ECCV2024｜AIGC(图像生成，视频生成，3D生成等)相关论文汇总（附论文链接/开源代码）【持续更新】

ECCV2024｜AIGC相关论文汇总（如果觉得有帮助，欢迎点赞和收藏）

  • Awesome-ECCV2024-AIGC
  • 1.图像生成(Image Generation/Image Synthesis)
      • Accelerating Diffusion Sampling with Optimized Time Steps
      • AnyControl: Create Your Artwork with Versatile Control on Text-to-Image Generation
      • A Watermark-Conditioned Diffusion Model for IP Protection
      • BeyondScene: Higher-Resolution Human-Centric Scene Generation With Pretrained Diffusion
      • ComFusion: Personalized Subject Generation in Multiple Specific Scenes From Single Image
      • Data Augmentation for Saliency Prediction via Latent Diffusion
      • Defect Spectrum: A Granular Look of Large-Scale Defect Datasets with Rich Semantics
      • DiffFAS: Face Anti-Spoofing via Generative Diffusion Models
      • DiffiT: Diffusion Vision Transformers for Image Generation
      • Large-scale Reinforcement Learning for Diffusion Models
      • MasterWeaver: Taming Editability and Identity for Personalized Text-to-Image Generation
      • Memory-Efficient Fine-Tuning for Quantized Diffusion Model
      • OMG: Occlusion-friendly Personalized Multi-concept Generation in Diffusion Models
      • Switch Diffusion Transformer: Synergizing Denoising Tasks with Sparse Mixture-of-Experts
  • 2.图像编辑(Image Editing)
      • A Task is Worth One Word: Learning with Task Prompts for High-Quality Versatile Image Inpainting
      • BrushNet: A Plug-and-Play Image Inpainting Model with Decomposed Dual-Branch Diffusion
      • FlexiEdit: Frequency-Aware Latent Refinement for Enhanced Non-Rigid Editing
      • StableDrag: Stable Dragging for Point-based Image Editing
      • TinyBeauty: Toward Tiny and High-quality Facial Makeup with Data Amplify Learning
  • 3.视频生成(Video Generation/Video Synthesis)
      • Audio-Synchronized Visual Animation
      • Dyadic Interaction Modeling for Social Behavior Generation
      • EDTalk: Efficient Disentanglement for Emotional Talking Head Synthesis
      • FreeInit : Bridging Initialization Gap in Video Diffusion Models
      • MOFA-Video: Controllable Image Animation via Generative Motion Field Adaptions in Frozen Image-to-Video Diffusion Model
      • ZeroI2V: Zero-Cost Adaptation of Pre-trained Transformers from Image to Video
  • 4.视频编辑(Video Editing)
      • Be-Your-Outpainter: Mastering Video Outpainting through Input-Specific Adaptation
      • DragAnything: Motion Control for Anything using Entity Representation
  • 5.3D生成(3D Generation/3D Synthesis)
      • EchoScene: Indoor Scene Generation via Information Echo over Scene Graph Diffusion
      • GenerateCT: Text-Conditional Generation of 3D Chest CT Volumes
      • GVGEN:Text-to-3D Generation with Volumetric Representation
      • Motion Mamba: Efficient and Long Sequence Motion Generation with Hierarchical and Bidirectional Selective SSM
      • ParCo: Part-Coordinating Text-to-Motion Synthesis
      • Surf-D: Generating High-Quality Surfaces of Arbitrary Topologies Using Diffusion Models
  • 6.3D编辑(3D Editing)
      • Gaussian Grouping: Segment and Edit Anything in 3D Scenes
      • SC4D: Sparse-Controlled Video-to-4D Generation and Motion Transfer
      • Texture-GS: Disentangling the Geometry and Texture for 3D Gaussian Splatting Editing
  • 7.多模态大语言模型(Multi-Modal Large Language Models)
      • An Image is Worth 1/2 Tokens After Layer 2: Plug-and-Play Inference Acceleration for Large Vision-Language Models
      • ControlCap: Controllable Region-level Captioning
      • DriveLM: Driving with Graph Visual Question Answering
      • Elysium: Exploring Object-level Perception in Videos via MLLM
      • Empowering Multimodal Large Language Model as a Powerful Data Generator
      • GiT: Towards Generalist Vision Transformer through Universal Language Interface
      • How Many Unicorns Are in This Image? A Safety Evaluation Benchmark for Vision LLMs
      • Long-CLIP: Unlocking the Long-Text Capability of CLIP
      • MathVerse: Does Your Multi-modal LLM Truly See the Diagrams in Visual Math Problems?
      • Merlin:Empowering Multimodal LLMs with Foresight Minds
      • Meta-Prompting for Automating Zero-shot Visual Recognition with LLMs
      • MM-SafetyBench: A Benchmark for Safety Evaluation of Multimodal Large Language Models
      • PointLLM: Empowering Large Language Models to Understand Point Clouds
      • R2-Bench: Benchmarking the Robustness of Referring Perception Models under Perturbations
      • SAM4MLLM: Enhance Multi-Modal Large Language Model for Referring Expression Segmentation
      • ShareGPT4V: Improving Large Multi-Modal Models with Better Captions
      • ST-LLM: Large Language Models Are Effective Temporal Learners
      • TTD: Text-Tag Self-Distillation Enhancing Image-Text Alignment in CLIP to Alleviate Single Tag Bias
      • UniIR: Training and Benchmarking Universal Multimodal Information Retrievers
  • 8.其他任务(Others)
  • 参考
  • 相关整理

Awesome-ECCV2024-AIGC

A Collection of Papers and Codes for ECCV2024 AIGC

整理汇总下2024年ECCV AIGC相关的论文和代码，具体如下。

欢迎star，fork和PR~
优先在Github更新：Awesome-ECCV2024-AIGC，欢迎star~
知乎：https://zhuanlan.zhihu.com/p/706699484

参考或转载请注明出处

ECCV2024官网：https://eccv.ecva.net/

ECCV接收论文列表：

ECCV完整论文库：

开会时间：2024年9月29日-10月4日

论文接收公布时间：2024年

【Contents】

  • 1.图像生成(Image Generation/Image Synthesis)
  • 2.图像编辑（Image Editing)
  • 3.视频生成(Video Generation/Image Synthesis)
  • 4.视频编辑(Video Editing)
  • 5.3D生成(3D Generation/3D Synthesis)
  • 6.3D编辑(3D Editing)
  • 7.多模态大语言模型(Multi-Modal Large Language Model)
  • 8.其他多任务(Others)

1.图像生成(Image Generation/Image Synthesis)

Accelerating Diffusion Sampling with Optimized Time Steps

  • Paper: https://arxiv.org/abs/2402.17376
  • Code: https://github.com/scxue/DM-NonUniform

AnyControl: Create Your Artwork with Versatile Control on Text-to-Image Generation

  • Paper: https://arxiv.org/abs/2406.18958
  • Code: https://github.com/open-mmlab/AnyControl

A Watermark-Conditioned Diffusion Model for IP Protection

  • Paper:
  • Code: https://github.com/rmin2000/WaDiff

BeyondScene: Higher-Resolution Human-Centric Scene Generation With Pretrained Diffusion

  • Paper: https://arxiv.org/abs/2404.04544
  • Code: https://github.com/gwang-kim/BeyondScene

ComFusion: Personalized Subject Generation in Multiple Specific Scenes From Single Image

  • Paper: https://arxiv.org/abs/2402.11849
  • Code:

Data Augmentation for Saliency Prediction via Latent Diffusion

  • Paper:
  • Code: https://github.com/IVRL/AugSal

Defect Spectrum: A Granular Look of Large-Scale Defect Datasets with Rich Semantics

  • Paper: https://arxiv.org/abs/2310.17316
  • Code: https://github.com/EnVision-Research/Defect_Spectrum

DiffFAS: Face Anti-Spoofing via Generative Diffusion Models

  • Paper:
  • Code: https://github.com/murphytju/DiffFAS

DiffiT: Diffusion Vision Transformers for Image Generation

  • Paper: https://arxiv.org/abs/2312.02139
  • Code: https://github.com/NVlabs/DiffiT

Large-scale Reinforcement Learning for Diffusion Models

  • Paper: https://arxiv.org/abs/2401.12244
  • Code: https://github.com/pinterest/atg-research/tree/main/joint-rl-diffusion

MasterWeaver: Taming Editability and Identity for Personalized Text-to-Image Generation

  • Paper: https://arxiv.org/abs/2405.05806
  • Code: https://github.com/csyxwei/MasterWeaver

Memory-Efficient Fine-Tuning for Quantized Diffusion Model

  • Paper:
  • Code: https://github.com/ugonfor/TuneQDM

OMG: Occlusion-friendly Personalized Multi-concept Generation in Diffusion Models

  • Paper: https://arxiv.org/abs/2403.10983
  • Code: https://github.com/kongzhecn/OMG

Switch Diffusion Transformer: Synergizing Denoising Tasks with Sparse Mixture-of-Experts

  • Paper: https://arxiv.org/abs/2403.09176
  • Code: https://github.com/byeongjun-park/Switch-DiT

2.图像编辑(Image Editing)

A Task is Worth One Word: Learning with Task Prompts for High-Quality Versatile Image Inpainting

  • Paper: https://arxiv.org/abs/2312.03594
  • Code: https://github.com/open-mmlab/PowerPaint

BrushNet: A Plug-and-Play Image Inpainting Model with Decomposed Dual-Branch Diffusion

  • Paper: https://arxiv.org/abs/2403.06976
  • Code: https://github.com/TencentARC/BrushNet

FlexiEdit: Frequency-Aware Latent Refinement for Enhanced Non-Rigid Editing

  • Paper:
  • Code: https://github.com/kookie12/FlexiEdit

StableDrag: Stable Dragging for Point-based Image Editing

  • Paper: https://arxiv.org/abs/2403.04437
  • Code:

TinyBeauty: Toward Tiny and High-quality Facial Makeup with Data Amplify Learning

  • Paper: https://arxiv.org/abs/2403.15033
  • Code: https://github.com/TinyBeauty/TinyBeauty

3.视频生成(Video Generation/Video Synthesis)

Audio-Synchronized Visual Animation

  • Paper: https://arxiv.org/abs/2403.05659
  • Code: https://github.com/lzhangbj/ASVA

Dyadic Interaction Modeling for Social Behavior Generation

  • Paper: https://arxiv.org/abs/2403.09069
  • Code: https://github.com/Boese0601/Dyadic-Interaction-Modeling

EDTalk: Efficient Disentanglement for Emotional Talking Head Synthesis

  • Paper: https://arxiv.org/abs/2404.01647
  • Code: https://github.com/tanshuai0219/EDTalk

FreeInit : Bridging Initialization Gap in Video Diffusion Models

  • Paper: https://arxiv.org/abs/2312.07537
  • Code: https://github.com/TianxingWu/FreeInit

MOFA-Video: Controllable Image Animation via Generative Motion Field Adaptions in Frozen Image-to-Video Diffusion Model

  • Paper: https://arxiv.org/abs/2405.20222
  • Code: https://github.com/MyNiuuu/MOFA-Video

ZeroI2V: Zero-Cost Adaptation of Pre-trained Transformers from Image to Video

  • Paper: https://arxiv.org/abs/2310.01324
  • Code:

4.视频编辑(Video Editing)

Be-Your-Outpainter: Mastering Video Outpainting through Input-Specific Adaptation

  • Paper: https://arxiv.org/abs/2403.13745
  • Code: https://github.com/G-U-N/Be-Your-Outpainter

DragAnything: Motion Control for Anything using Entity Representation

  • Paper: https://arxiv.org/abs/2403.07420
  • Code: https://github.com/showlab/DragAnything

5.3D生成(3D Generation/3D Synthesis)

EchoScene: Indoor Scene Generation via Information Echo over Scene Graph Diffusion

  • Paper: https://arxiv.org/abs/2405.00915
  • Code: https://github.com/ymxlzgy/echoscene

GenerateCT: Text-Conditional Generation of 3D Chest CT Volumes

  • Paper: https://arxiv.org/abs/2405.00915
  • Code: https://github.com/ibrahimethemhamamci/GenerateCT

GVGEN:Text-to-3D Generation with Volumetric Representation

  • Paper:
  • Code: https://github.com/SOTAMak1r/GVGEN

Motion Mamba: Efficient and Long Sequence Motion Generation with Hierarchical and Bidirectional Selective SSM

  • Paper: https://arxiv.org/abs/2403.07487
  • Code: https://github.com/steve-zeyu-zhang/MotionMamba

ParCo: Part-Coordinating Text-to-Motion Synthesis

  • Paper: https://arxiv.org/abs/2403.18512
  • Code: https://github.com/qrzou/ParCo

Surf-D: Generating High-Quality Surfaces of Arbitrary Topologies Using Diffusion Models

  • Paper: https://arxiv.org/abs/2311.17050
  • Code: https://github.com/Yzmblog/SurfD

6.3D编辑(3D Editing)

Gaussian Grouping: Segment and Edit Anything in 3D Scenes

  • Paper: https://arxiv.org/abs/2312.00732
  • Code: https://github.com/lkeab/gaussian-grouping

SC4D: Sparse-Controlled Video-to-4D Generation and Motion Transfer

  • Paper: https://arxiv.org/abs/2403.18512
  • Code: https://github.com/JarrentWu1031/SC4D

Texture-GS: Disentangling the Geometry and Texture for 3D Gaussian Splatting Editing

  • Paper: https://arxiv.org/abs/2403.10050
  • Code: https://github.com/slothfulxtx/Texture-GS

7.多模态大语言模型(Multi-Modal Large Language Models)

An Image is Worth 1/2 Tokens After Layer 2: Plug-and-Play Inference Acceleration for Large Vision-Language Models

  • Paper: https://arxiv.org/abs/2403.06764
  • Code: https://github.com/pkunlp-icler/FastV

ControlCap: Controllable Region-level Captioning

  • Paper: https://arxiv.org/abs/2401.17910
  • Code: https://github.com/callsys/ControlCap

DriveLM: Driving with Graph Visual Question Answering

  • Paper: https://arxiv.org/abs/2312.14150
  • Code: https://github.com/OpenDriveLab/DriveLM

Elysium: Exploring Object-level Perception in Videos via MLLM

  • Paper: https://arxiv.org/abs/2403.16558
  • Code: https://github.com/Hon-Wong/Elysium

Empowering Multimodal Large Language Model as a Powerful Data Generator

  • Paper:
  • Code: https://github.com/zhaohengyuan1/Genixer

GiT: Towards Generalist Vision Transformer through Universal Language Interface

  • Paper: https://arxiv.org/abs/2403.09394
  • Code: https://github.com/Haiyang-W/GiT

How Many Unicorns Are in This Image? A Safety Evaluation Benchmark for Vision LLMs

  • Paper: https://arxiv.org/abs/2311.17600
  • Code: https://github.com/UCSC-VLAA/vllm-safety-benchmark

Long-CLIP: Unlocking the Long-Text Capability of CLIP

  • Paper: https://arxiv.org/abs/2403.15378
  • Code: https://github.com/beichenzbc/Long-CLIP

MathVerse: Does Your Multi-modal LLM Truly See the Diagrams in Visual Math Problems?

  • Paper: https://arxiv.org/abs/2403.14624
  • Code: https://github.com/ZrrSkywalker/MathVerse

Merlin:Empowering Multimodal LLMs with Foresight Minds

  • Paper: https://arxiv.org/abs/2312.00589
  • Code: https://github.com/Ahnsun/merlin

Meta-Prompting for Automating Zero-shot Visual Recognition with LLMs

  • Paper: https://arxiv.org/abs/2403.11755
  • Code: https://github.com/jmiemirza/Meta-Prompting

MM-SafetyBench: A Benchmark for Safety Evaluation of Multimodal Large Language Models

  • Paper: https://arxiv.org/abs/2403.14624
  • Code: https://github.com/isXinLiu/MM-SafetyBench

PointLLM: Empowering Large Language Models to Understand Point Clouds

  • Paper: https://arxiv.org/abs/2308.16911
  • Code: https://github.com/OpenRobotLab/PointLLM

R2-Bench: Benchmarking the Robustness of Referring Perception Models under Perturbations

  • Paper: https://arxiv.org/abs/2403.04924
  • Code: https://github.com/lxa9867/r2bench

SAM4MLLM: Enhance Multi-Modal Large Language Model for Referring Expression Segmentation

  • Paper:
  • Code: https://github.com/AI-Application-and-Integration-Lab/SAM4MLLM

ShareGPT4V: Improving Large Multi-Modal Models with Better Captions

  • Paper: https://arxiv.org/abs/2311.12793
  • Code: https://github.com/ShareGPT4Omni/ShareGPT4V

ST-LLM: Large Language Models Are Effective Temporal Learners

  • Paper: https://arxiv.org/abs/2404.00308
  • Code: https://github.com/TencentARC/ST-LLM

TTD: Text-Tag Self-Distillation Enhancing Image-Text Alignment in CLIP to Alleviate Single Tag Bias

  • Paper: https://arxiv.org/abs/2404.00384
  • Code: https://github.com/shjo-april/TTD

UniIR: Training and Benchmarking Universal Multimodal Information Retrievers

  • Paper: https://arxiv.org/abs/2311.17136
  • Code: https://github.com/TIGER-AI-Lab/UniIR

8.其他任务(Others)

持续更新~

参考

相关整理

  • Awesome-CVPR2024-AIGC
  • Awesome-AIGC-Research-Groups
  • Awesome-Low-Level-Vision-Research-Groups
  • Awesome-CVPR2024-CVPR2021-CVPR2020-Low-Level-Vision
  • Awesome-ECCV2020-Low-Level-Vision

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