ICCV2023-Papers-with-Code

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

2160 papers accepted！

ICCV 2023 收录论文IDs：https://t.co/A0mCH8gbOi

注1：欢迎各位大佬提交issue，分享ICCV 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

ICCV 2021

如果你想了解最新最优质的的CV论文、开源项目和学习资料，欢迎扫码加入【CVer学术交流群】！互相学习，一起进步~

【ICCV 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)
• 视频实例分割(Video Instance Segmentation)
• 参考图像分割(Referring Image Segmentation)
• 图像抠图(Image Matting)
• Low-level Vision
• 超分辨率(Super-Resolution)
• 去噪(Denoising)
• 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语义场景补全(3D Semantic Scene Completion)
• 3D配准(3D Registration)
• 3D人体姿态估计(3D Human Pose Estimation)
• 3D人体Mesh估计(3D Human Mesh Estimation)
• 医学图像(Medical Image)
• 图像生成(Image Generation)
• 视频生成(Video Generation)
• 图像编辑(Image Editing)
• 视频编辑(Video Editing)
• 视频理解(Video Understanding)
• 人体运动生成(Human Motion Generation)
• 低光照图像增强(Low-light Image Enhancement)
• 图像检索(Image Retrieval)
• 图像融合(Image Fusion)
• 其它(Others)

Avatars

Transforming Text into Neural Human Avatars with Parameterized Shape and Pose Control

Paper: https://arxiv.org/abs/2303.17606

Code: https://github.com/songrise/AvatarCraft

Backbone

Rethinking Mobile Block for Efficient Attention-based Models

• Paper: https://arxiv.org/abs/2301.01146
• Code: https://github.com/zhangzjn/EMO

NeRF

IntrinsicNeRF: Learning Intrinsic Neural Radiance Fields for Editable Novel View Synthesis

• Homepage: https://zju3dv.github.io/intrinsic_nerf/
• Paper: https://arxiv.org/abs/2210.00647
• Code: https://github.com/zju3dv/IntrinsicNeRF

Transforming Text into Neural Human Avatars with Parameterized Shape and Pose Control

Paper: https://arxiv.org/abs/2303.17606

Code: https://github.com/songrise/AvatarCraft

Diffusion Models(扩散模型)

PoseDiffusion: Solving Pose Estimation via Diffusion-aided Bundle Adjustment

• Paper: https://arxiv.org/abs/2306.15667
• Code: https://github.com/facebookresearch/PoseDiffusion

FreeDoM: Training-Free Energy-Guided Conditional Diffusion Model

• Paper: https://arxiv.org/abs/2303.09833
• Code: https://github.com/vvictoryuki/FreeDoM

BoxDiff: Text-to-Image Synthesis with Training-Free Box-Constrained Diffusion

• Paper: https://arxiv.org/abs/2307.10816
• Code: https://github.com/Sierkinhane/BoxDiff

BeLFusion: Latent Diffusion for Behavior-Driven Human Motion Prediction

• Paper: https://arxiv.org/abs/2211.14304
• Code: https://github.com/BarqueroGerman/BeLFusion

DDFM: Denoising Diffusion Model for Multi-Modality Image Fusion

• Paper: https://arxiv.org/abs/2303.06840
• Code: https://github.com/Zhaozixiang1228/MMIF-DDFM

目标检测(Object Detection)

Femtodet: an object detection baseline for energy versus performance tradeoffs

• Paper: https://arxiv.org/abs/2301.06719
• Code: https://github.com/yh-pengtu/FemtoDet

Group DETR: Fast DETR Training with Group-Wise One-to-Many Assignment

• Paper: https://arxiv.org/abs/2207.13085
• Code: https://github.com/Atten4Vis/GroupDETR

目标跟踪(Visual Tracking)

Cross-modal Orthogonal High-rank Augmentation for RGB-Event Transformer-trackers

• Paper: https://arxiv.org/abs/2307.04129
• Code: https://github.com/ZHU-Zhiyu/High-Rank_RGB-Event_Tracker

语义分割(Semantic Segmentation)

Segment Anything

• Homepage: https://segment-anything.com/
• Paper: https://arxiv.org/abs/2304.02643
• Code: https://github.com/facebookresearch/segment-anything

MARS: Model-agnostic Biased Object Removal without Additional Supervision for Weakly-Supervised Semantic Segmentation

• Paper: https://arxiv.org/abs/2304.09913
• Code: https://github.com/shjo-april/MARS

FreeCOS: Self-Supervised Learning from Fractals and Unlabeled Images for Curvilinear Object Segmentation

• Paper: https://arxiv.org/abs/2307.07245
• Code: https://github.com/TY-Shi/FreeCOS

视频实例分割(Video Instance Segmentation)

DVIS: Decoupled Video Instance Segmentation Framework

• Paper: https://arxiv.org/abs/2306.03413
• Code: https://github.com/zhang-tao-whu/DVIS

Low-level Vision

Self-supervised Learning to Bring Dual Reversed Rolling Shutter Images Alive

• Paper: https://arxiv.org/abs/2305.19862
• Code: https://github.com/shangwei5/SelfDRSC

3D点云(3D Point Cloud)

Robo3D: Towards Robust and Reliable 3D Perception against Corruptions

• Homepage: https://ldkong.com/Robo3D
• Paper: https://arxiv.org/abs/2303.17597
• Code: https://github.com/ldkong1205/Robo3D

3D目标检测(3D Object Detection)

PETRv2: A Unified Framework for 3D Perception from Multi-Camera Images

• Paper: https://arxiv.org/abs/2206.01256
• Code: https://github.com/megvii-research/PETR

DQS3D: Densely-matched Quantization-aware Semi-supervised 3D Detection

• Paper: https://arxiv.org/abs/2304.13031
• Code: https://github.com/AIR-DISCOVER/DQS3D

SparseFusion: Fusing Multi-Modal Sparse Representations for Multi-Sensor 3D Object Detection

• Paper: https://arxiv.org/abs/2304.14340
• Code: https://github.com/yichen928/SparseFusion

StreamPETR: Exploring Object-Centric Temporal Modeling for Efficient Multi-View 3D Object Detection

• Paper: https://arxiv.org/abs/2303.11926
• Code: https://github.com/exiawsh/StreamPETR.git

Cross Modal Transformer: Towards Fast and Robust 3D Object Detection

• Paper: https://arxiv.org/abs/2301.01283
• Code: https://github.com/junjie18/CMT.git

MetaBEV: Solving Sensor Failures for BEV Detection and Map Segmentation

• Paper: https://arxiv.org/abs/2304.09801
• Project: https://chongjiange.github.io/metabev.html
• Code: https://github.com/ChongjianGE/MetaBEV

Revisiting Domain-Adaptive 3D Object Detection by Reliable, Diverse and Class-balanced Pseudo-Labeling

• Paper: https://arxiv.org/abs/2307.07944
• Code: https://github.com/zhuoxiao-chen/ReDB-DA-3Ddet

3D语义分割(3D Semantic Segmentation)

Rethinking Range View Representation for LiDAR Segmentation

• Homepage: https://ldkong.com/RangeFormer
• Paper: https://arxiv.org/abs/2303.05367
• Code: None

3D目标跟踪(3D Object Tracking)

MBPTrack: Improving 3D Point Cloud Tracking with Memory Networks and Box Priors

• Paper: https://arxiv.org/abs/2303.05071
• Code : https://github.com/slothfulxtx/MBPTrack3D

视频理解(Video Understanding)

Unmasked Teacher: Towards Training-Efficient Video Foundation Models

• Paper: https://arxiv.org/abs/2303.16058

• Code: https://github.com/OpenGVLab/unmasked_teacher

图像生成(Image Generation)

FreeDoM: Training-Free Energy-Guided Conditional Diffusion Model

• Paper: https://arxiv.org/abs/2303.09833
• Code: https://github.com/vvictoryuki/FreeDoM

BoxDiff: Text-to-Image Synthesis with Training-Free Box-Constrained Diffusion

• Paper: https://arxiv.org/abs/2307.10816
• Code: https://github.com/Sierkinhane/BoxDiff

视频生成(Video Generation)

Simulating Fluids in Real-World Still Images

• Homepage: https://slr-sfs.github.io/
• Paper: https://arxiv.org/abs/2204.11335
• Code: https://github.com/simon3dv/SLR-SFS

图像编辑(Image Editing)

Multimodal Garment Designer: Human-Centric Latent Diffusion Models for Fashion Image Editing

• Paper: https://arxiv.org/abs/2304.02051
• Code: https://github.com/aimagelab/multimodal-garment-designer

视频编辑(Video Editing)

FateZero: Fusing Attentions for Zero-shot Text-based Video Editing

• Project: https://fate-zero-edit.github.io/
• Paper: https://arxiv.org/abs/2303.09535
• Code: https://github.com/ChenyangQiQi/FateZero

人体运动生成(Human Motion Generation)

BeLFusion: Latent Diffusion for Behavior-Driven Human Motion Prediction

• Paper: https://arxiv.org/abs/2211.14304
• Code: https://github.com/BarqueroGerman/BeLFusion

低光照图像增强(Low-light Image Enhancement)

Implicit Neural Representation for Cooperative Low-light Image Enhancement

• Paper: https://arxiv.org/abs/2303.11722
• Code: https://github.com/Ysz2022/NeRCo

图像检索(Image Retrieval)

Zero-Shot Composed Image Retrieval with Textual Inversion

• Paper: https://arxiv.org/abs/2303.15247
• Code: https://github.com/miccunifi/SEARLE

图像融合(Image Fusion)

DDFM: Denoising Diffusion Model for Multi-Modality Image Fusion

• Paper: https://arxiv.org/abs/2303.06840
• Code: https://github.com/Zhaozixiang1228/MMIF-DDFM

其它(Others)

MotionBERT: A Unified Perspective on Learning Human Motion Representations

• Homepage: https://motionbert.github.io/
• Paper: https://arxiv.org/abs/2210.06551
• Code: https://github.com/Walter0807/MotionBERT