CVPR 2023 论文和开源项目合集(Papers with Code)

CVPR 2023 论文和开源项目合集(papers with code)！

25.78% = 2360 / 9155

CVPR2023 decisions are now available on OpenReview! This year, wereceived a record number of 9155 submissions (a 12% increase over CVPR2022), and accepted 2360 papers, for a 25.78% acceptance rate.

注1：欢迎各位大佬提交issue，分享CVPR 2023论文和开源项目！

注2：关于往年CV顶会论文以及其他优质CV论文和大盘点，详见： https://github.com/amusi/daily-paper-computer-vision

· CVPR 2019

· CVPR 2020

· CVPR 2021

· CVPR 2022

【CVPR 2023 论文开源目录】

· Backbone

· CLIP

· MAE

· GAN

· GNN

· MLP

· NAS

· OCR

· NeRF

· DETR

· Prompt

· Diffusion Models(扩散模型)

· Avatars

· ReID(重识别)

· 长尾分布(Long-Tail)

· Vision Transformer

· 视觉和语言(Vision-Language)

· 自监督学习(Self-supervised Learning)

· 数据增强(Data Augmentation)

· 目标检测(Object Detection)

· 目标跟踪(Visual Tracking)

· 语义分割(Semantic Segmentation)

· 实例分割(Instance Segmentation)

· 全景分割(Panoptic Segmentation)

· 医学图像分割(Medical Image Segmentation)

· 视频目标分割(Video Object Segmentation)

· 参考图像分割(Referring Image Segmentation)

· 图像抠图(Image Matting)

· 图像编辑(Image Editing)

· Low-level Vision

· 超分辨率(Super-Resolution)

· 去模糊(Deblur)

· 3D点云(3D Point Cloud)

· 3D目标检测(3D Object Detection)

· 3D语义分割(3D Semantic Segmentation)

· 3D目标跟踪(3D Object Tracking)

· 3D人体姿态估计(3D Human Pose Estimation)

· 3D语义场景补全(3D Semantic Scene Completion)

· 3D配准(3D Registration)

· 医学图像(Medical Image)

· 图像生成(Image Generation)

· 视频生成(Video Generation)

· 视频理解(Video Understanding)

· 行为检测(Action Detection)

· 文本检测(Text Detection)

· 知识蒸馏(Knowledge Distillation)

· 模型剪枝(Model Pruning)

· 图像压缩(Image Compression)

· 异常检测(Anomaly Detection)

· 三维重建(3D Reconstruction)

· 深度估计(Depth Estimation)

· 轨迹预测(Trajectory Prediction)

· 车道线检测(Lane Detection)

· 图像描述(Image Captioning)

· 视觉问答(Visual Question Answering)

· 手语识别(Sign Language Recognition)

· 视频预测(Video Prediction)

· 新视点合成(Novel View Synthesis)

· Zero-Shot Learning(零样本学习)

· 立体匹配(Stereo Matching)

· 场景图生成(Scene Graph Generation)

· 隐式神经表示(Implicit Neural Representations)

· 图像质量评价(Image Quality Assessment)

· 数据集(Datasets)

· 新任务(New Tasks)

· 其他(Others)

Backbone

Integrally Pre-Trained Transformer Pyramid Networks

· Paper: https://arxiv.org/abs/2211.12735

· Code: https://github.com/sunsmarterjie/iTPN

Stitchable Neural Networks

· Homepage: https://snnet.github.io/

· Paper: https://arxiv.org/abs/2302.06586

· Code: https://github.com/ziplab/SN-Net

Run, Don't Walk: Chasing Higher FLOPS for Faster Neural Networks

· Paper: https://arxiv.org/abs/2303.03667

· Code: https://github.com/JierunChen/FasterNet

BiFormer: Vision Transformer with Bi-Level Routing Attention

· Paper: None

· Code: https://github.com/rayleizhu/BiFormer

DeepMAD: Mathematical Architecture Design for Deep Convolutional Neural Network

· Paper: https://arxiv.org/abs/2303.02165

· Code: https://github.com/alibaba/lightweight-neural-architecture-search

Vision Transformer with Super Token Sampling

· Paper: https://arxiv.org/abs/2211.11167

· Code: https://github.com/hhb072/SViT

Hard Patches Mining for Masked Image Modeling

· Paper: None

· Code: None

SMPConv: Self-moving Point Representations for Continuous Convolution

· Paper: https://arxiv.org/abs/2304.02330

· Code: https://github.com/sangnekim/SMPConv

CLIP

GALIP: Generative Adversarial CLIPs for Text-to-Image Synthesis

· Paper: https://arxiv.org/abs/2301.12959

· Code: https://github.com/tobran/GALIP

DeltaEdit: Exploring Text-free Training for Text-driven Image Manipulation

· Paper: https://arxiv.org/abs/2303.06285

· Code: https://github.com/Yueming6568/DeltaEdit

MAE

Learning 3D Representations from 2D Pre-trained Models via Image-to-Point Masked Autoencoders

· Paper: https://arxiv.org/abs/2212.06785

· Code: https://github.com/ZrrSkywalker/I2P-MAE

Generic-to-Specific Distillation of Masked Autoencoders

· Paper: https://arxiv.org/abs/2302.14771

· Code: https://github.com/pengzhiliang/G2SD

GAN

DeltaEdit: Exploring Text-free Training for Text-driven Image Manipulation

· Paper: https://arxiv.org/abs/2303.06285

· Code: https://github.com/Yueming6568/DeltaEdit

NeRF

NoPe-NeRF: Optimising Neural Radiance Field with No Pose Prior

· Home: https://nope-nerf.active.vision/

· Paper: https://arxiv.org/abs/2212.07388

· Code: None

Latent-NeRF for Shape-Guided Generation of 3D Shapes and Textures

· Paper: https://arxiv.org/abs/2211.07600

· Code: https://github.com/eladrich/latent-nerf

NeRF in the Palm of Your Hand: Corrective Augmentation for Robotics via Novel-View Synthesis

· Paper: https://arxiv.org/abs/2301.08556

· Code: None

Panoptic Lifting for 3D Scene Understanding with Neural Fields

· Homepage: https://nihalsid.github.io/panoptic-lifting/

· Paper: https://arxiv.org/abs/2212.09802

· Code: None

NeRFLiX: High-Quality Neural View Synthesis by Learning a Degradation-Driven Inter-viewpoint MiXer

· Homepage: https://redrock303.github.io/nerflix/

· Paper: https://arxiv.org/abs/2303.06919

· Code: None

HNeRV: A Hybrid Neural Representation for Videos

· Homepage: https://haochen-rye.github.io/HNeRV

· Paper: https://arxiv.org/abs/2304.02633

· Code: https://github.com/haochen-rye/HNeRV

DETR

DETRs with Hybrid Matching

· Paper: https://arxiv.org/abs/2207.13080

· Code: https://github.com/HDETR

Prompt

Diversity-Aware Meta Visual Prompting

· Paper: https://arxiv.org/abs/2303.08138

· Code: https://github.com/shikiw/DAM-VP

NAS

PA&DA: Jointly Sampling PAth and DAta for Consistent NAS

· Paper: https://arxiv.org/abs/2302.14772

· Code: https://github.com/ShunLu91/PA-DA

Avatars

Structured 3D Features for Reconstructing Relightable and Animatable Avatars

· Homepage: https://enriccorona.github.io/s3f/

· Paper: https://arxiv.org/abs/2212.06820

· Code: None

· Demo: https://www.youtube.com/watch?v=mcZGcQ6L-2s

Learning Personalized High Quality Volumetric Head Avatars from Monocular RGB Videos

· Homepage: https://augmentedperception.github.io/monoavatar/

· Paper: https://arxiv.org/abs/2304.01436

ReID(重识别)

Clothing-Change Feature Augmentation for Person Re-Identification

· Paper: None

· Code: None

MSINet: Twins Contrastive Search of Multi-Scale Interaction for Object ReID

· Paper: https://arxiv.org/abs/2303.07065

· Code: https://github.com/vimar-gu/MSINet

Shape-Erased Feature Learning for Visible-Infrared Person Re-Identification

· Paper: https://arxiv.org/abs/2304.04205

· Code: None

Diffusion Models(扩散模型)

Video Probabilistic Diffusion Models in Projected Latent Space

· Homepage: https://sihyun.me/PVDM/

· Paper: https://arxiv.org/abs/2302.07685

· Code: https://github.com/sihyun-yu/PVDM

Solving 3D Inverse Problems using Pre-trained 2D Diffusion Models

· Paper: https://arxiv.org/abs/2211.10655

· Code: None

Imagic: Text-Based Real Image Editing with Diffusion Models

· Homepage: https://imagic-editing.github.io/

· Paper: https://arxiv.org/abs/2210.09276

· Code: None

Parallel Diffusion Models of Operator and Image for Blind Inverse Problems

· Paper: https://arxiv.org/abs/2211.10656

· Code: None

DiffRF: Rendering-guided 3D Radiance Field Diffusion

· Homepage: https://sirwyver.github.io/DiffRF/

· Paper: https://arxiv.org/abs/2212.01206

· Code: None

MM-Diffusion: Learning Multi-Modal Diffusion Models for Joint Audio and Video Generation

· Paper: https://arxiv.org/abs/2212.09478

· Code: https://github.com/researchmm/MM-Diffusion

HouseDiffusion: Vector Floorplan Generation via a Diffusion Model with Discrete and Continuous Denoising

· Homepage: https://aminshabani.github.io/housediffusion/

· Paper: https://arxiv.org/abs/2211.13287

· Code: https://github.com/aminshabani/house_diffusion

TrojDiff: Trojan Attacks on Diffusion Models with Diverse Targets

· Paper: https://arxiv.org/abs/2303.05762

· Code: https://github.com/chenweixin107/TrojDiff

Back to the Source: Diffusion-Driven Adaptation to Test-Time Corruption

· Paper: https://arxiv.org/abs/2207.03442

· Code: https://github.com/shiyegao/DDA

DR2: Diffusion-based Robust Degradation Remover for Blind Face Restoration

· Paper: https://arxiv.org/abs/2303.06885

· Code: None

Trace and Pace: Controllable Pedestrian Animation via Guided Trajectory Diffusion

· Homepage: https://nv-tlabs.github.io/trace-pace/

· Paper: https://arxiv.org/abs/2304.01893

· Code: None

Generative Diffusion Prior for Unified Image Restoration and Enhancement

· Paper: https://arxiv.org/abs/2304.01247

· Code: None

Conditional Image-to-Video Generation with Latent Flow Diffusion Models

· Paper: https://arxiv.org/abs/2303.13744

· Code: https://github.com/nihaomiao/CVPR23_LFDM

长尾分布(Long-Tail)

Long-Tailed Visual Recognition via Self-Heterogeneous Integration with Knowledge Excavation

· Paper: https://arxiv.org/abs/2304.01279

· Code: None

Vision Transformer

Integrally Pre-Trained Transformer Pyramid Networks

· Paper: https://arxiv.org/abs/2211.12735

· Code: https://github.com/sunsmarterjie/iTPN

Mask3D: Pre-training 2D Vision Transformers by Learning Masked 3D Priors

· Homepage: https://niessnerlab.org/projects/hou2023mask3d.html

· Paper: https://arxiv.org/abs/2302.14746

· Code: None

Learning Trajectory-Aware Transformer for Video Super-Resolution

· Paper: https://arxiv.org/abs/2204.04216

· Code: https://github.com/researchmm/TTVSR

Vision Transformers are Parameter-Efficient Audio-Visual Learners

· Homepage: https://yanbo.ml/project_page/LAVISH/

· Code: https://github.com/GenjiB/LAVISH

Where We Are and What We're Looking At: Query Based Worldwide Image Geo-localization Using Hierarchies and Scenes

· Paper: https://arxiv.org/abs/2303.04249

· Code: None

DSVT: Dynamic Sparse Voxel Transformer with Rotated Sets

· Paper: https://arxiv.org/abs/2301.06051

· Code: https://github.com/Haiyang-W/DSVT

DeepSolo: Let Transformer Decoder with Explicit Points Solo for Text Spotting

· Paper: https://arxiv.org/abs/2211.10772

· Code link: https://github.com/ViTAE-Transformer/DeepSolo

BiFormer: Vision Transformer with Bi-Level Routing Attention

· Paper: https://arxiv.org/abs/2303.08810

· Code: https://github.com/rayleizhu/BiFormer

Vision Transformer with Super Token Sampling

· Paper: https://arxiv.org/abs/2211.11167

· Code: https://github.com/hhb072/SViT

BEVFormer v2: Adapting Modern Image Backbones to Bird's-Eye-View Recognition via Perspective Supervision

· Paper: https://arxiv.org/abs/2211.10439

· Code: None

BAEFormer: Bi-directional and Early Interaction Transformers for Bird’s Eye View Semantic Segmentation

· Paper: None

· Code: None

Visual Dependency Transformers: Dependency Tree Emerges from Reversed Attention

· Paper: https://arxiv.org/abs/2304.03282

· Code: None

视觉和语言(Vision-Language)

GIVL: Improving Geographical Inclusivity of Vision-Language Models with Pre-Training Methods

· Paper: https://arxiv.org/abs/2301.01893

· Code: None

Teaching Structured Vision&Language Concepts to Vision&Language Models

· Paper: https://arxiv.org/abs/2211.11733

· Code: None

Uni-Perceiver v2: A Generalist Model for Large-Scale Vision and Vision-Language Tasks

· Paper: https://arxiv.org/abs/2211.09808

· Code: https://github.com/fundamentalvision/Uni-Perceiver

Towards Generalisable Video Moment Retrieval: Visual-Dynamic Injection to Image-Text Pre-Training

· Paper: https://arxiv.org/abs/2303.00040

· Code: None

CapDet: Unifying Dense Captioning and Open-World Detection Pretraining

· Paper: https://arxiv.org/abs/2303.02489

· Code: None

FAME-ViL: Multi-Tasking Vision-Language Model for Heterogeneous Fashion Tasks

· Paper: https://arxiv.org/abs/2303.02483

· Code: None

Meta-Explore: Exploratory Hierarchical Vision-and-Language Navigation Using Scene Object Spectrum Grounding

· Homepage: https://rllab-snu.github.io/projects/Meta-Explore/doc.html

· Paper: https://arxiv.org/abs/2303.04077

· Code: None

All in One: Exploring Unified Video-Language Pre-training

· Paper: https://arxiv.org/abs/2203.07303

· Code: https://github.com/showlab/all-in-one

Position-guided Text Prompt for Vision Language Pre-training

· Paper: https://arxiv.org/abs/2212.09737

· Code: https://github.com/sail-sg/ptp

EDA: Explicit Text-Decoupling and Dense Alignment for 3D Visual Grounding

· Paper: https://arxiv.org/abs/2209.14941

· Code: https://github.com/yanmin-wu/EDA

CapDet: Unifying Dense Captioning and Open-World Detection Pretraining

· Paper: https://arxiv.org/abs/2303.02489

· Code: None

FAME-ViL: Multi-Tasking Vision-Language Model for Heterogeneous Fashion Tasks

· Paper: https://arxiv.org/abs/2303.02483

· Code: https://github.com/BrandonHanx/FAME-ViL

Align and Attend: Multimodal Summarization with Dual Contrastive Losses

· Homepage: https://boheumd.github.io/A2Summ/

· Paper: https://arxiv.org/abs/2303.07284

· Code: https://github.com/boheumd/A2Summ

Multi-Modal Representation Learning with Text-Driven Soft Masks

· Paper: https://arxiv.org/abs/2304.00719

· Code: None

Learning to Name Classes for Vision and Language Models

· Paper: https://arxiv.org/abs/2304.01830

· Code: None

目标检测(Object Detection)

YOLOv7: Trainable bag-of-freebies sets new state-of-the-art for real-time object detectors

· Paper: https://arxiv.org/abs/2207.02696

· Code: https://github.com/WongKinYiu/yolov7

DETRs with Hybrid Matching

· Paper: https://arxiv.org/abs/2207.13080

· Code: https://github.com/HDETR

Enhanced Training of Query-Based Object Detection via Selective Query Recollection

· Paper: https://arxiv.org/abs/2212.07593

· Code: https://github.com/Fangyi-Chen/SQR

Object-Aware Distillation Pyramid for Open-Vocabulary Object Detection

· Paper: https://arxiv.org/abs/2303.05892

· Code: https://github.com/LutingWang/OADP

目标跟踪(Object Tracking)

Simple Cues Lead to a Strong Multi-Object Tracker

· Paper: https://arxiv.org/abs/2206.04656

· Code: None

语义分割(Semantic Segmentation)

Efficient Semantic Segmentation by Altering Resolutions for Compressed Videos

· Paper: https://arxiv.org/abs/2303.07224

· Code: https://github.com/THU-LYJ-Lab/AR-Seg

FREDOM: Fairness Domain Adaptation Approach to Semantic Scene Understanding

· Paper: https://arxiv.org/abs/2304.02135

· Code: https://github.com/uark-cviu/FREDOM

医学图像分割(Medical Image Segmentation)

Label-Free Liver Tumor Segmentation

· Paper: https://arxiv.org/abs/2303.14869

· Code: https://github.com/MrGiovanni/SyntheticTumors

Directional Connectivity-based Segmentation of Medical Images

· Paper: https://arxiv.org/abs/2304.00145

· Code: https://github.com/Zyun-Y/DconnNet

Bidirectional Copy-Paste for Semi-Supervised Medical Image Segmentation

· Paper: https://arxiv.org/abs/2305.00673

· Code: https://github.com/DeepMed-Lab-ECNU/BCP

Devil is in the Queries: Advancing Mask Transformers for Real-world Medical Image Segmentation and Out-of-Distribution Localization

· Paper: https://arxiv.org/abs/2304.00212

· Code: None

Fair Federated Medical Image Segmentation via Client Contribution Estimation

· Paper: https://arxiv.org/abs/2303.16520

· Code: https://github.com/NVIDIA/NVFlare/tree/dev/research/fed-ce

Ambiguous Medical Image Segmentation using Diffusion Models

· Homepage: https://aimansnigdha.github.io/cimd/

· Paper: https://arxiv.org/abs/2304.04745

· Code: https://github.com/aimansnigdha/Ambiguous-Medical-Image-Segmentation-using-Diffusion-Models

Orthogonal Annotation Benefits Barely-supervised Medical Image Segmentation

· Paper: https://arxiv.org/abs/2303.13090

· Code: https://github.com/HengCai-NJU/DeSCO

MagicNet: Semi-Supervised Multi-Organ Segmentation via Magic-Cube Partition and Recovery

· Paper: https://arxiv.org/abs/2301.01767

· Code: https://github.com/DeepMed-Lab-ECNU/MagicNet

MCF: Mutual Correction Framework for Semi-Supervised Medical Image Segmentation

· Paper: None

· Code: None

Rethinking Few-Shot Medical Segmentation: A Vector Quantization View

· Paper: None

· Code: None

Pseudo-label Guided Contrastive Learning for Semi-supervised Medical Image Segmentation

· Paper: None

· Code: None

SDC-UDA: Volumetric Unsupervised Domain Adaptation Framework for Slice-Direction Continuous Cross-Modality Medical Image Segmentation

· Paper: None

· Code: None

视频目标分割（Video Object Segmentation）

Two-shot Video Object Segmentation

· Paper: https://arxiv.org/abs/2303.12078

· Code: https://github.com/yk-pku/Two-shot-Video-Object-Segmentation

Under Video Object Segmentation Section

· Paper: https://arxiv.org/abs/2303.07815

· Code: None

参考图像分割(Referring Image Segmentation )

PolyFormer: Referring Image Segmentation as Sequential Polygon Generation

·

Paper: https://arxiv.org/abs/2302.07387

·

·

Code: None

·

3D点云(3D-Point-Cloud)

Physical-World Optical Adversarial Attacks on 3D Face Recognition

· Paper: https://arxiv.org/abs/2205.13412

· Code: https://github.com/PolyLiYJ/SLAttack.git

IterativePFN: True Iterative Point Cloud Filtering

· Paper: https://arxiv.org/abs/2304.01529

· Code: https://github.com/ddsediri/IterativePFN

3D目标检测(3D Object Detection)

DSVT: Dynamic Sparse Voxel Transformer with Rotated Sets

· Paper: https://arxiv.org/abs/2301.06051

· Code: https://github.com/Haiyang-W/DSVT

FrustumFormer: Adaptive Instance-aware Resampling for Multi-view 3D Detection

· Paper: https://arxiv.org/abs/2301.04467

· Code: None

3D Video Object Detection with Learnable Object-Centric Global Optimization

· Paper: None

· Code: None

Hierarchical Supervision and Shuffle Data Augmentation for 3D Semi-Supervised Object Detection

· Paper: https://arxiv.org/abs/2304.01464

· Code: https://github.com/azhuantou/HSSDA

3D语义分割(3D Semantic Segmentation)

Less is More: Reducing Task and Model Complexity for 3D Point Cloud Semantic Segmentation

· Paper: https://arxiv.org/abs/2303.11203

· Code: https://github.com/l1997i/lim3d

3D语义场景补全(3D Semantic Scene Completion)

· Paper: https://arxiv.org/abs/2302.12251

· Code: https://github.com/NVlabs/VoxFormer

3D配准(3D Registration)

Robust Outlier Rejection for 3D Registration with Variational Bayes

· Paper: https://arxiv.org/abs/2304.01514

· Code: https://github.com/Jiang-HB/VBReg

Low-level Vision

Causal-IR: Learning Distortion Invariant Representation for Image Restoration from A Causality Perspective

· Paper: https://arxiv.org/abs/2303.06859

· Code: https://github.com/lixinustc/Casual-IR-DIL

Burstormer: Burst Image Restoration and Enhancement Transformer

· Paper: https://arxiv.org/abs/2304.01194

· Code: http://github.com/akshaydudhane16/Burstormer

超分辨率(Video Super-Resolution)

Super-Resolution Neural Operator

· Paper: https://arxiv.org/abs/2303.02584

· Code: https://github.com/2y7c3/Super-Resolution-Neural-Operator

视频超分辨率

Learning Trajectory-Aware Transformer for Video Super-Resolution

·

Paper: https://arxiv.org/abs/2204.04216

·

·

Code: https://github.com/researchmm/TTVSR

·

图像生成(Image Generation)

GALIP: Generative Adversarial CLIPs for Text-to-Image Synthesis

· Paper: https://arxiv.org/abs/2301.12959

· Code: https://github.com/tobran/GALIP

MAGE: MAsked Generative Encoder to Unify Representation Learning and Image Synthesis

· Paper: https://arxiv.org/abs/2211.09117

· Code: https://github.com/LTH14/mage

Toward Verifiable and Reproducible Human Evaluation for Text-to-Image Generation

· Paper: https://arxiv.org/abs/2304.01816

· Code: None

Few-shot Semantic Image Synthesis with Class Affinity Transfer

· Paper: https://arxiv.org/abs/2304.02321

· Code: None

TopNet: Transformer-based Object Placement Network for Image Compositing

· Paper: https://arxiv.org/abs/2304.03372

· Code: None

视频生成(Video Generation)

MM-Diffusion: Learning Multi-Modal Diffusion Models for Joint Audio and Video Generation

· Paper: https://arxiv.org/abs/2212.09478

· Code: https://github.com/researchmm/MM-Diffusion

Conditional Image-to-Video Generation with Latent Flow Diffusion Models

· Paper: https://arxiv.org/abs/2303.13744

· Code: https://github.com/nihaomiao/CVPR23_LFDM

视频理解(Video Understanding)

Learning Transferable Spatiotemporal Representations from Natural Script Knowledge

· Paper: https://arxiv.org/abs/2209.15280

· Code: https://github.com/TencentARC/TVTS

Frame Flexible Network

· Paper: https://arxiv.org/abs/2303.14817

· Code: https://github.com/BeSpontaneous/FFN

Masked Motion Encoding for Self-Supervised Video Representation Learning

· Paper: https://arxiv.org/abs/2210.06096

· Code: https://github.com/XinyuSun/MME

行为检测(Action Detection)

TriDet: Temporal Action Detection with Relative Boundary Modeling

· Paper: https://arxiv.org/abs/2303.07347

· Code: https://github.com/dingfengshi/TriDet

文本检测(Text Detection)

DeepSolo: Let Transformer Decoder with Explicit Points Solo for Text Spotting

· Paper: https://arxiv.org/abs/2211.10772

· Code link: https://github.com/ViTAE-Transformer/DeepSolo

知识蒸馏(Knowledge Distillation)

Learning to Retain while Acquiring: Combating Distribution-Shift in Adversarial Data-Free Knowledge Distillation

· Paper: https://arxiv.org/abs/2302.14290

· Code: None

Generic-to-Specific Distillation of Masked Autoencoders

· Paper: https://arxiv.org/abs/2302.14771

· Code: https://github.com/pengzhiliang/G2SD

模型剪枝(Model Pruning)

DepGraph: Towards Any Structural Pruning

· Paper: https://arxiv.org/abs/2301.12900

· Code: https://github.com/VainF/Torch-Pruning

图像压缩(Image Compression)

Context-Based Trit-Plane Coding for Progressive Image Compression

· Paper: https://arxiv.org/abs/2303.05715

· Code: https://github.com/seungminjeon-github/CTC

异常检测(Anomaly Detection)

Deep Feature In-painting for Unsupervised Anomaly Detection in X-ray Images

· Paper: https://arxiv.org/abs/2111.13495

· Code: https://github.com/tiangexiang/SQUID

三维重建(3D Reconstruction)

OReX: Object Reconstruction from Planar Cross-sections Using Neural Fields

· Paper: https://arxiv.org/abs/2211.12886

· Code: None

SparsePose: Sparse-View Camera Pose Regression and Refinement

· Paper: https://arxiv.org/abs/2211.16991

· Code: None

NeuDA: Neural Deformable Anchor for High-Fidelity Implicit Surface Reconstruction

· Paper: https://arxiv.org/abs/2303.02375

· Code: None

Vid2Avatar: 3D Avatar Reconstruction from Videos in the Wild via Self-supervised Scene Decomposition

· Homepage: https://moygcc.github.io/vid2avatar/

· Paper: https://arxiv.org/abs/2302.11566

· Code: https://github.com/MoyGcc/vid2avatar

· Demo: https://youtu.be/EGi47YeIeGQ

To fit or not to fit: Model-based Face Reconstruction and Occlusion Segmentation from Weak Supervision

· Paper: https://arxiv.org/abs/2106.09614

· Code: https://github.com/unibas-gravis/Occlusion-Robust-MoFA

Structural Multiplane Image: Bridging Neural View Synthesis and 3D Reconstruction

· Paper: https://arxiv.org/abs/2303.05937

· Code: None

3D Cinemagraphy from a Single Image

· Homepage: https://xingyi-li.github.io/3d-cinemagraphy/

· Paper: https://arxiv.org/abs/2303.05724

· Code: https://github.com/xingyi-li/3d-cinemagraphy

Revisiting Rotation Averaging: Uncertainties and Robust Losses

· Paper: https://arxiv.org/abs/2303.05195

· Code https://github.com/zhangganlin/GlobalSfMpy

FFHQ-UV: Normalized Facial UV-Texture Dataset for 3D Face Reconstruction

· Paper: https://arxiv.org/abs/2211.13874

· Code: https://github.com/csbhr/FFHQ-UV

A Hierarchical Representation Network for Accurate and Detailed Face Reconstruction from In-The-Wild Images

·

Homepage: https://younglbw.github.io/HRN-homepage/

·

·

Paper: https://arxiv.org/abs/2302.14434

·

·

Code: https://github.com/youngLBW/HRN

·

深度估计(Depth Estimation)

Lite-Mono: A Lightweight CNN and Transformer Architecture for Self-Supervised Monocular Depth Estimation

· Paper: https://arxiv.org/abs/2211.13202

· Code: https://github.com/noahzn/Lite-Mono

轨迹预测(Trajectory Prediction)

IPCC-TP: Utilizing Incremental Pearson Correlation Coefficient for Joint Multi-Agent Trajectory Prediction

· Paper: https://arxiv.org/abs/2303.00575

· Code: None

EqMotion: Equivariant Multi-agent Motion Prediction with Invariant Interaction Reasoning

· Paper: https://arxiv.org/abs/2303.10876

· Code: https://github.com/MediaBrain-SJTU/EqMotion

车道线检测(Lane Detection)

Anchor3DLane: Learning to Regress 3D Anchors for Monocular 3D Lane Detection

· Paper: https://arxiv.org/abs/2301.02371

· Code: https://github.com/tusen-ai/Anchor3DLane

BEV-LaneDet: An Efficient 3D Lane Detection Based on Virtual Camera via Key-Points

· Paper: https://arxiv.org/abs/2210.06006v3

· Code: https://github.com/gigo-team/bev_lane_det

图像描述(Image Captioning)

ConZIC: Controllable Zero-shot Image Captioning by Sampling-Based Polishing

· Paper: https://arxiv.org/abs/2303.02437

· Code: Node

Cross-Domain Image Captioning with Discriminative Finetuning

· Paper: https://arxiv.org/abs/2304.01662

· Code: None

Model-Agnostic Gender Debiased Image Captioning

· Paper: https://arxiv.org/abs/2304.03693

· Code: None

视觉问答(Visual Question Answering)

MixPHM: Redundancy-Aware Parameter-Efficient Tuning for Low-Resource Visual Question Answering

· Paper: https://arxiv.org/abs/2303.01239

· Code: https://github.com/jingjing12110/MixPHM

手语识别(Sign Language Recognition)

Continuous Sign Language Recognition with Correlation Network

Paper: https://arxiv.org/abs/2303.03202

Code: https://github.com/hulianyuyy/CorrNet

视频预测(Video Prediction)

MOSO: Decomposing MOtion, Scene and Object for Video Prediction

· Paper: https://arxiv.org/abs/2303.03684

· Code: https://github.com/anonymous202203/MOSO

新视点合成(Novel View Synthesis)

3D Video Loops from Asynchronous Input

· Homepage: https://limacv.github.io/VideoLoop3D_web/

· Paper: https://arxiv.org/abs/2303.05312

· Code: https://github.com/limacv/VideoLoop3D

Zero-Shot Learning(零样本学习)

Bi-directional Distribution Alignment for Transductive Zero-Shot Learning

· Paper: https://arxiv.org/abs/2303.08698

· Code: https://github.com/Zhicaiwww/Bi-VAEGAN

Semantic Prompt for Few-Shot Learning

· Paper: None

· Code: None

立体匹配(Stereo Matching)

Iterative Geometry Encoding Volume for Stereo Matching

· Paper: https://arxiv.org/abs/2303.06615

· Code: https://github.com/gangweiX/IGEV

Learning the Distribution of Errors in Stereo Matching for Joint Disparity and Uncertainty Estimation

· Paper: https://arxiv.org/abs/2304.00152

· Code: None

场景图生成(Scene Graph Generation)

Prototype-based Embedding Network for Scene Graph Generation

· Paper: https://arxiv.org/abs/2303.07096

· Code: None

隐式神经表示(Implicit Neural Representations)

Polynomial Implicit Neural Representations For Large Diverse Datasets

· Paper: https://arxiv.org/abs/2303.11424

· Code: https://github.com/Rajhans0/Poly_INR

图像质量评价(Image Quality Assessment)

Re-IQA: Unsupervised Learning for Image Quality Assessment in the Wild

· Paper: https://arxiv.org/abs/2304.00451

· Code: None

数据集(Datasets)

Human-Art: A Versatile Human-Centric Dataset Bridging Natural and Artificial Scenes

· Paper: https://arxiv.org/abs/2303.02760

· Code: None

Align and Attend: Multimodal Summarization with Dual Contrastive Losses

· Homepage: https://boheumd.github.io/A2Summ/

· Paper: https://arxiv.org/abs/2303.07284

· Code: https://github.com/boheumd/A2Summ

GeoNet: Benchmarking Unsupervised Adaptation across Geographies

· Homepage: https://tarun005.github.io/GeoNet/

· Paper: https://arxiv.org/abs/2303.15443

CelebV-Text: A Large-Scale Facial Text-Video Dataset

· Homepage: https://celebv-text.github.io/

· Paper: https://arxiv.org/abs/2303.14717

其他(Others)

Interactive Segmentation as Gaussian Process Classification

· Paper: https://arxiv.org/abs/2302.14578

· Code: None

Backdoor Attacks Against Deep Image Compression via Adaptive Frequency Trigger

· Paper: https://arxiv.org/abs/2302.14677

· Code: None

SplineCam: Exact Visualization and Characterization of Deep Network Geometry and Decision Boundaries

· Homepage: http://bit.ly/splinecam

· Paper: https://arxiv.org/abs/2302.12828

· Code: None

SCOTCH and SODA: A Transformer Video Shadow Detection Framework

· Paper: https://arxiv.org/abs/2211.06885

· Code: None

DeepMapping2: Self-Supervised Large-Scale LiDAR Map Optimization

· Homepage: https://ai4ce.github.io/DeepMapping2/

· Paper: https://arxiv.org/abs/2212.06331

· None: https://github.com/ai4ce/DeepMapping2

RelightableHands: Efficient Neural Relighting of Articulated Hand Models

· Homepage: https://sh8.io/#/relightable_hands

· Paper: https://arxiv.org/abs/2302.04866

· Code: None

Token Turing Machines

· Paper: https://arxiv.org/abs/2211.09119

· Code: None

Single Image Backdoor Inversion via Robust Smoothed Classifiers

· Paper: https://arxiv.org/abs/2303.00215

· Code: https://github.com/locuslab/smoothinv

To fit or not to fit: Model-based Face Reconstruction and Occlusion Segmentation from Weak Supervision

· Paper: https://arxiv.org/abs/2106.09614

· Code: https://github.com/unibas-gravis/Occlusion-Robust-MoFA

HOOD: Hierarchical Graphs for Generalized Modelling of Clothing Dynamics

· Homepage: https://dolorousrtur.github.io/hood/

· Paper: https://arxiv.org/abs/2212.07242

· Code: https://github.com/dolorousrtur/hood

· Demo: https://www.youtube.com/watch?v=cBttMDPrUYY

A Whac-A-Mole Dilemma: Shortcuts Come in Multiples Where Mitigating One Amplifies Others

· Paper: https://arxiv.org/abs/2212.04825

· Code: https://github.com/facebookresearch/Whac-A-Mole.git

RelightableHands: Efficient Neural Relighting of Articulated Hand Models

· Homepage: https://sh8.io/#/relightable_hands

· Paper: https://arxiv.org/abs/2302.04866

· Code: None

· Demo: https://sh8.io/static/media/teacher_video.923d87957fe0610730c2.mp4

Neuro-Modulated Hebbian Learning for Fully Test-Time Adaptation

· Paper: https://arxiv.org/abs/2303.00914

· Code: None

Demystifying Causal Features on Adversarial Examples and Causal Inoculation for Robust Network by Adversarial Instrumental Variable Regression

· Paper: https://arxiv.org/abs/2303.01052

· Code: None

UniDexGrasp: Universal Robotic Dexterous Grasping via Learning Diverse Proposal Generation and Goal-Conditioned Policy

· Paper: https://arxiv.org/abs/2303.00938

· Code: None

Disentangling Orthogonal Planes for Indoor Panoramic Room Layout Estimation with Cross-Scale Distortion Awareness

· Paper: https://arxiv.org/abs/2303.00971

· Code: https://github.com/zhijieshen-bjtu/DOPNet

Learning Neural Parametric Head Models

· Homepage: https://simongiebenhain.github.io/NPHM)

· Paper: https://arxiv.org/abs/2212.02761

· Code: None

A Meta-Learning Approach to Predicting Performance and Data Requirements

· Paper: https://arxiv.org/abs/2303.01598

· Code: None

MACARONS: Mapping And Coverage Anticipation with RGB Online Self-Supervision

· Homepage: https://imagine.enpc.fr/~guedona/MACARONS/

· Paper: https://arxiv.org/abs/2303.03315

· Code: None

Masked Images Are Counterfactual Samples for Robust Fine-tuning

· Paper: https://arxiv.org/abs/2303.03052

· Code: None

HairStep: Transfer Synthetic to Real Using Strand and Depth Maps for Single-View 3D Hair Modeling

· Paper: https://arxiv.org/abs/2303.02700

· Code: None

Decompose, Adjust, Compose: Effective Normalization by Playing with Frequency for Domain Generalization

· Paper: https://arxiv.org/abs/2303.02328

· Code: None

Gradient Norm Aware Minimization Seeks First-Order Flatness and Improves Generalization

· Paper: https://arxiv.org/abs/2303.03108

· Code: None

Unlearnable Clusters: Towards Label-agnostic Unlearnable Examples

· Paper: https://arxiv.org/abs/2301.01217

· Code: https://github.com/jiamingzhang94/Unlearnable-Clusters

Where We Are and What We're Looking At: Query Based Worldwide Image Geo-localization Using Hierarchies and Scenes

· Paper: https://arxiv.org/abs/2303.04249

· Code: None

UniHCP: A Unified Model for Human-Centric Perceptions

· Paper: https://arxiv.org/abs/2303.02936

· Code: https://github.com/OpenGVLab/UniHCP

CUDA: Convolution-based Unlearnable Datasets

· Paper: https://arxiv.org/abs/2303.04278

· Code: https://github.com/vinusankars/Convolution-based-Unlearnability

Masked Images Are Counterfactual Samples for Robust Fine-tuning

· Paper: https://arxiv.org/abs/2303.03052

· Code: None

AdaptiveMix: Robust Feature Representation via Shrinking Feature Space

· Paper: https://arxiv.org/abs/2303.01559

· Code: https://github.com/WentianZhang-ML/AdaptiveMix

Physical-World Optical Adversarial Attacks on 3D Face Recognition

· Paper: https://arxiv.org/abs/2205.13412

· Code: https://github.com/PolyLiYJ/SLAttack.git

DPE: Disentanglement of Pose and Expression for General Video Portrait Editing

· Paper: https://arxiv.org/abs/2301.06281

· Code: https://carlyx.github.io/DPE/

SadTalker: Learning Realistic 3D Motion Coefficients for Stylized Audio-Driven Single Image Talking Face Animation

· Paper: https://arxiv.org/abs/2211.12194

· Code: https://github.com/Winfredy/SadTalker

Intrinsic Physical Concepts Discovery with Object-Centric Predictive Models

· Paper: None

· Code: None

Sharpness-Aware Gradient Matching for Domain Generalization

· Paper: None

· Code: https://github.com/Wang-pengfei/SAGM

Mind the Label-shift for Augmentation-based Graph Out-of-distribution Generalization

· Paper: None

· Code: None

Blind Video Deflickering by Neural Filtering with a Flawed Atlas

· Homepage: https://chenyanglei.github.io/deflicker

· Paper: None

· Code: None

RiDDLE: Reversible and Diversified De-identification with Latent Encryptor

· Paper: None

· Code: https://github.com/ldz666666/RiDDLE

PoseExaminer: Automated Testing of Out-of-Distribution Robustness in Human Pose and Shape Estimation

· Paper: https://arxiv.org/abs/2303.07337

· Code: None

Upcycling Models under Domain and Category Shift

· Paper: https://arxiv.org/abs/2303.07110

· Code: https://github.com/ispc-lab/GLC

Modality-Agnostic Debiasing for Single Domain Generalization

· Paper: https://arxiv.org/abs/2303.07123

· Code: None

Progressive Open Space Expansion for Open-Set Model Attribution

· Paper: https://arxiv.org/abs/2303.06877

· Code: None

Dynamic Neural Network for Multi-Task Learning Searching across Diverse Network Topologies

· Paper: https://arxiv.org/abs/2303.06856

· Code: None

GFPose: Learning 3D Human Pose Prior with Gradient Fields

· Paper: https://arxiv.org/abs/2212.08641

· Code: https://github.com/Embracing/GFPose

PRISE: Demystifying Deep Lucas-Kanade with Strongly Star-Convex Constraints for Multimodel Image Alignment

· Paper: https://arxiv.org/abs/2303.11526

· Code: https://github.com/Zhang-VISLab

Sketch2Saliency: Learning to Detect Salient Objects from Human Drawings

· Paper: https://arxiv.org/abs/2303.11502

· Code: None

Boundary Unlearning

· Paper: https://arxiv.org/abs/2303.11570

· Code: None

ImageNet-E: Benchmarking Neural Network Robustness via Attribute Editing

· Paper: https://arxiv.org/abs/2303.17096

· Code: https://github.com/alibaba/easyrobust

Zero-shot Model Diagnosis

· Paper: https://arxiv.org/abs/2303.15441

· Code: None

GeoNet: Benchmarking Unsupervised Adaptation across Geographies

· Homepage: https://tarun005.github.io/GeoNet/

· Paper: https://arxiv.org/abs/2303.15443

Quantum Multi-Model Fitting

· Paper: https://arxiv.org/abs/2303.15444

· Code: https://github.com/FarinaMatteo/qmmf

DivClust: Controlling Diversity in Deep Clustering

· Paper: https://arxiv.org/abs/2304.01042

· Code: None

Neural Volumetric Memory for Visual Locomotion Control

· Homepage: https://rchalyang.github.io/NVM

· Paper: https://arxiv.org/abs/2304.01201

· Code: https://rchalyang.github.io/NVM

MonoHuman: Animatable Human Neural Field from Monocular Video

· Homepage: https://yzmblog.github.io/projects/MonoHuman/

· Paper: https://arxiv.org/abs/2304.02001

· Code: https://github.com/Yzmblog/MonoHuman

Trace and Pace: Controllable Pedestrian Animation via Guided Trajectory Diffusion

· Homepage: https://nv-tlabs.github.io/trace-pace/

· Paper: https://arxiv.org/abs/2304.01893

· Code: None

Bridging the Gap between Model Explanations in Partially Annotated Multi-label Classification

· Paper: https://arxiv.org/abs/2304.01804

· Code: None

HyperCUT: Video Sequence from a Single Blurry Image using Unsupervised Ordering

· Paper: https://arxiv.org/abs/2304.01686

· Code: None

On the Stability-Plasticity Dilemma of Class-Incremental Learning

· Paper: https://arxiv.org/abs/2304.01663

· Code: None

Defending Against Patch-based Backdoor Attacks on Self-Supervised Learning

· Paper: https://arxiv.org/abs/2304.01482

· Code: None

VNE: An Effective Method for Improving Deep Representation by Manipulating Eigenvalue Distribution

· Paper: https://arxiv.org/abs/2304.01434

· Code: https://github.com/jaeill/CVPR23-VNE

Detecting and Grounding Multi-Modal Media Manipulation

· Homepage: https://rshaojimmy.github.io/Projects/MultiModal-DeepFake

· Paper: https://arxiv.org/abs/2304.02556

· Code: https://github.com/rshaojimmy/MultiModal-DeepFake

Meta-causal Learning for Single Domain Generalization

· Paper: https://arxiv.org/abs/2304.03709

· Code: None

Disentangling Writer and Character Styles for Handwriting Generation

· Paper: https://arxiv.org/abs/2303.14736

· Code: https://github.com/dailenson/SDT

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——注：以上为OpenAI ChatGPT自动分析结果，仅供参考