CVPR2026-Papers-with-Code

CVPR 2026 论文和开源项目合集

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README.md

CVPR 2026 论文和开源项目合集(Papers with Code)

CVPR 2026 decisions are now available on OpenReview!25.42% = 4090 / 16092


注1:欢迎各位大佬提交issue,分享CVPR 2026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 2025

- ECCV 2024


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【CVPR 2026 论文开源目录】

- 3DGS(Gaussian Splatting)
- Agent)
- Avatars
- Backbone
- CLIP
- Mamba
- Embodied AI
- GAN
- GNN
- 多模态大语言模型(MLLM)
- 大语言模型(LLM)
- 具身智能(Embodied AI)
- 空间智能(Spatial Intelligence
- NAS
- OCR
- NeRF
- DETR
- 扩散模型(Diffusion Models)
- 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)
- 异常检测(Anomaly 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(Medical Image)
- 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)
- 图像编辑(Image Editing)
- Low-level Vision
- 超分辨率(Super-Resolution)
- 去噪(Denoising)
- 去模糊(Deblur)
- 自动驾驶(Autonomous Driving)
- 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)
- 3D Visual Grounding(3D视觉定位)
- 医学图像(Medical Image)
- 图像生成(Image Generation)
- 视频生成(Video Generation)
- 3D生成(3D Generation)
- 视频理解(Video Understanding)
- 行为检测(Action Detection)
- 遥感(Remote)
- 文本检测(Text Detection)
- 知识蒸馏(Knowledge Distillation)
- 模型剪枝(Model Pruning)
- 图像压缩(Image Compression)
- 视频压缩(Video Compression)
- 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)
- 特征匹配(Feature Matching)
- 暗光图像增强(Low-light Image Enhancement)
- 场景图生成(Scene Graph Generation)
- 图像检索(Image Retrieval)
- 风格迁移(Style Transfer)
- 隐式神经表示(Implicit Neural Representations)
- 图像质量评价(Image Quality Assessment)
- 视频质量评价(Video Quality Assessment)
- 压缩感知(Compressive Sensing)
- 数据集(Datasets)
- 新任务(New Tasks)
- 其他(Others)

<a name="3DGS"></a>

3DGS(Gaussian Splatting)

Dropping Anchor and Spherical Harmonics for Sparse-view Gaussian Splatting

- Paper: https://arxiv.org/abs/2602.20933
- Code:
- Project: https://sk-fun.fun/DropAnSH-GS

Topology-Aware Gaussian Splatting for Dynamic Mesh Modeling and Tracking

- Paper: https://arxiv.org/abs/2512.01329
- Project: https://haza628.github.io/tagSplat/

FastGS: Training 3D Gaussian Splatting in 100 Seconds

- Paper: https://arxiv.org/pdf/2511.04283
- Code: https://github.com/fastgs/FastGS
- Project: https://fastgs.github.io/


<a name="Agent"></a>

Agent


<a name="Avatars"></a>

Avatars


Backbone


<a name="CLIP"></a>

CLIP

<a name="Mamba"></a>

Mamba

<a name="GAN"></a>

GAN

<a name="OCR"></a>

OCR


<a name="NeRF"></a>

NeRF

<a name="DETR"></a>

DETR


<a name="Prompt"></a>

Prompt

<a name="MLLM"></a>

多模态大语言模型(MLLM)

Circuit Tracing in Vision-Language Models: Understanding the Internal Mechanisms of Multimodal Thinking

- Paper: https://arxiv.org/abs/2602.20330
- Code: https://github.com/UIUC-MONET/vlm-circuit-tracing

UniM: A Unified Any-to-Any Interleaved Multimodal Benchmark

- Paper: https://arxiv.org/abs/2603.05075
- Code:
- Project: https://any2any-mllm.github.io/unim/

<a name="LLM"></a>

大语言模型(LLM)


<a name="Embodied-AI"></a>


具身智能(Embodied AI)

Wanderland: Geometrically Grounded Simulation for Open-World Embodied AI

- Paper: https://arxiv.org/abs/2511.20620
- Code: https://github.com/ai4ce/wanderland
- Project: https://ai4ce.github.io/wanderland/


<a name="SI"></a>


空间智能(Spatial Intelligence)

Spatial-SSRL: Enhancing Spatial Understanding via Self-Supervised Reinforcement Learning

- Paper: https://arxiv.org/abs/2510.27606
- Code: https://github.com/InternLM/Spatial-SSRL
- Model: https://huggingface.co/internlm/Spatial-SSRL-7B


<a name="NAS"></a>

NAS

<a name="ReID"></a>

ReID(重识别)


MOS: Mitigating Optical-SAR Modality Gap for Cross-Modal Ship Re-Identification

- Paper: https://arxiv.org/abs/2512.03404
- Code: https://github.com/yjzhao1019/MOS


<a name="Diffusion"></a>

扩散模型(Diffusion Models)

<a name="Vision-Transformer"></a>

Vision Transformer

<a name="VL"></a>

视觉和语言(Vision-Language)

StructXLIP: Enhancing Vision-language Models with Multimodal Structural Cues

- Paper: https://arxiv.org/abs/2602.20089
- Code: https://github.com/intelligolabs/StructXLIP

ApET: Approximation-Error Guided Token Compression for Efficient VLMs

- Paper: https://arxiv.org/abs/2602.19870
- Code: https://github.com/MaQianKun0/ApET

Circuit Tracing in Vision-Language Models: Understanding the Internal Mechanisms of Multimodal Thinking

- Paper: https://arxiv.org/abs/2602.20330
- Code: https://github.com/UIUC-MONET/vlm-circuit-tracing


<a name="Object-Detection"></a>

目标检测(Object Detection)


<a name="Anomaly-Detection"></a>

异常检测(Anomaly Detection)

<a name="VT"></a>

目标跟踪(Object Tracking)


<a name="MI"></a>

医学图像(Medical Image)

医学图像分割(Medical Image Segmentation)

MedCLIPSeg: Probabilistic Vision–Language Adaptation for Data-Efficient and Generalizable Medical Image Segmentation

- Paper: https://arxiv.org/abs/2602.20423
- Code: https://github.com/HealthX-Lab/MedCLIPSeg
- Project: https://tahakoleilat.github.io/MedCLIPSeg

<a name="Autonomous-Driving"></a>

自动驾驶(Autonomous Driving)

Open-Vocabulary Domain Generalization in Urban-Scene Segmentation

- Paper: https://arxiv.org/pdf/2602.18853
- Code: https://github.com/DZhaoXd/s2_corr

U4D: Uncertainty-Aware 4D World Modeling from LiDAR Sequences

- Paper: https://arxiv.org/abs/2512.02982
- Code: https://github.com/worldbench/U4D


3D点云(3D-Point-Cloud)

CLIPoint3D: Language-Grounded Few-Shot Unsupervised 3D Point Cloud Domain Adaptation

- Paper: https://arxiv.org/abs/2602.20409
- Code: https://github.com/SarthakM320/CLIPoint3D


<a name="3DOD"></a>

3D目标检测(3D Object Detection)

<a name="3DOD"></a>

3D语义分割(3D Semantic Segmentation)

<a name="LLV"></a>

Low-level Vision

<a name="SR"></a>

超分辨率(Super-Resolution)


<a name="Denoising"></a>

去噪(Denoising)

图像去噪(Image Denoising)

<a name="3D-Human-Pose-Estimation"></a>

3D人体姿态估计(3D Human Pose Estimation)

<a name="3DVG"></a>

#3D Visual Grounding(3D视觉定位)


<a name="Image-Generation"></a>

图像生成(Image Generation)


ExpPortrait: Expressive Portrait Generation via Personalized Representation

- Paper: https://arxiv.org/abs/2602.19900
- Code:


<a name="Video-Generation"></a>

视频生成(Video Generation)


<a name="Image-Editing"></a>

图像编辑(Image Editing)

<a name="Video-Editing"></a>

视频编辑(Video Editing)

<a name="3D-Generation"></a>

3D生成(3D Generation)


<a name="3D-Reconstruction"></a>

3D重建(3D Reconstruction)

tttLRM: Test-Time Training for Long Context and Autoregressive 3D Reconstruction

- Project: https://cwchenwang.github.io/tttLRM/
- Paper: https://arxiv.org/abs/2602.20160
- Code: https://github.com/cwchenwang/tttLRM

Flow3r: Factored Flow Prediction for Scalable Visual Geometry Learning

- Project: https://flow3r-project.github.io/
- Paper: https://arxiv.org/abs/2602.20157
- Code: https://github.com/Kidrauh/flow3r

RAP: Fast Feedforward Rendering-Free Attribute-Guided Primitive Importance Score Prediction for Efficient 3D Gaussian Splatting Processing

- Paper: https://arxiv.org/abs/2602.19753
- Code: https://github.com/yyyykf/RAP


<a name="HMG"></a>

人体运动生成(Human Motion Generation)

<a name="Video-Understanding"></a>

视频理解(Video Understanding)

<a name="Remote"></a>

遥感(Remote)

Brewing Stronger Features: Dual-Teacher Distillation for Multispectral Earth Observation

- Paper: https://arxiv.org/abs/2602.19863
- Code: None


<a name="KD"></a>

知识蒸馏(Knowledge Distillation)

<a name="Depth-Estimation"></a>


深度估计(Depth Estimation)


<a name="Stereo-Matching"></a>

立体匹配(Stereo Matching)


<a name="Low-light"></a>

暗光图像增强(Low-light Image Enhancement)

<a name="IC"></a>

图像压缩(Image Compression)](#IC)

<a name="VC"></a>

视频压缩(Video Compression)](#VC)

UniComp: Rethinking Video Compression Through Informational Uniqueness

- Paper: https://arxiv.org/abs/2512.03575
- Code: https://github.com/TimeMarker-LLM/UniComp

<a name="SGG"></a>

场景图生成(Scene Graph Generation)


<a name="Image-Retrieval"></a>

图像检索(Image Retrieval)

PinPoint: Evaluation of Composed Image Retrieval with Explicit Negatives, Multi-Image Queries, and Paraphrase Testing

- Paper: https://arxiv.org/abs/2603.04598
- Code:


<a name="ST"></a>

风格迁移(Style Transfer)

<a name="IQA"></a>

图像质量评价(Image Quality Assessment)

<a name="Video-Quality-Assessment"></a>

视频质量评价(Video Quality Assessment)

<a name="CS"></a>

压缩感知(Compressive Sensing)

<a name="Datasets"></a>

数据集(Datasets)


<a name="Others"></a>

其他(Others)

Decoupling Defense Strategies for Robust Image Watermarking

- Paper: https://arxiv.org/abs/2602.20053
- Code: None

Multi-Modal Representation Learning via Semi-Supervised Rate Reduction for Generalized Category Discovery

- Paper: https://arxiv.org/abs/2602.19910
- Code:

The Invisible Gorilla Effect in Out-of-distribution Detection

- Paper: https://arxiv.org/abs/2602.20068
- Code: https://github.com/HarryAnthony/Invisible_Gorilla_Effect

SimLBR: Learning to Detect Fake Images by Learning to Detect Real Images

- Paper: https://arxiv.org/abs/2602.20412
- Code:

RecoverMark: Robust Watermarking for Localization and Recovery of Manipulated Faces

- Paper: https://arxiv.org/abs/2602.20618
- Code:

Probing and Bridging Geometry-Interaction Cues for Affordance Reasoning in Vision Foundation Models

- Paper:
- Code:

GEM-TFL: Bridging Weak and Full Supervision for Forgery Localization through EM-Guided Decomposition and Temporal Refinement

- Paper: https://arxiv.org/abs/2603.05095
- Code:


FOZO: Forward-Only Zeroth-Order Prompt Optimization for Test-Time Adaptation

- Paper: https://arxiv.org/abs/2603.04733
- Code: https://github.com/eVI-group-SCU/FOZO

Mitigating Instance Entanglement in Instance-Dependent Partial Label Learning

- Paper: https://arxiv.org/abs/2603.04825
- Code: https://github.com/RyanZhaoIc/CAD