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https://github.com/haofanwang/awesome-conditional-content-generation

Update-to-data resources for conditional content generation, including human motion generation, image or video generation and editing.
https://github.com/haofanwang/awesome-conditional-content-generation
List: awesome-conditional-content-generation
aigc awesome-list conditional-generation controllable-generation cross-modality diffusion-models
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Update-to-data resources for conditional content generation, including human motion generation, image or video generation and editing.
Host: GitHub
URL: https://github.com/haofanwang/awesome-conditional-content-generation
Owner: haofanwang
Created: 2022-11-27T10:27:25.000Z (almost 2 years ago)
Default Branch: main
Last Pushed: 2023-09-06T06:19:26.000Z (about 1 year ago)
Last Synced: 2024-05-23T10:00:47.956Z (5 months ago)
Topics: aigc, awesome-list, conditional-generation, controllable-generation, cross-modality, diffusion-models
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Forks: 22
Open Issues: 1
Metadata Files:
- Readme: README.md
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README

        # awesome-conditional-content-generation [![Awesome](https://awesome.re/badge.svg)](https://awesome.re)

This repository contains a collection of resources and papers on ***Conditional Content Generation***. Especially for human motion generation, image generation and video generation. This repo is maintained by [Haofan Wang](https://github.com/haofanwang).

如果你对可控内容生成（2D/3D）方向感兴趣，希望与我保持更广泛的学术合作或寻求一份实习，并且已经发表过至少一篇顶会论文，欢迎随时发邮件至[email protected]，高校、工业界均欢迎。

## Contents

- Papers List

  - [Tracking Papers on Diffusion Models](https://vsehwag.github.io/blog/2023/2/all_papers_on_diffusion.html)

  - Conditional Human Motion Generation

    - [Music-Driven motion generation](#music-driven-motion-generation)

    - [Text-Driven motion generation](#text-driven-motion-generation)

    - [Audio-Driven motion generation](#audio-driven-motion-generation)

    - [Human Motion Prediction](#human-motion-prediction)

    - [Motion Applications](#motion-applications)

  - Conditional Image Generation

    - [Text-Image Generation](#text-image-generation)

    - [Text-3D Image Generation](#text-3d-image-generation)

  - Conditional Video Generation

    - [Text-Video Generation](#text-video-generation)

## Papers

### Music-Driven motion generation

[Taming Diffusion Models for Music-driven Conducting Motion Generation](https://arxiv.org/abs/2306.10065) \

NUS, AAAI 2023 Summer Symposium, [[Code]](https://github.com/viiika/Diffusion-Conductor)

[Music-Driven Group Choreography](http://128.84.21.203/abs/2303.12337) \

AIOZ AI, CVPR'23

[Discrete Contrastive Diffusion for Cross-Modal and Conditional Generation](https://github.com/L-YeZhu/CDCD) \

Illinois Institute of Technology, ICLR'23, [[Code]](https://github.com/L-YeZhu/CDCD)

[Magic: Multi Art Genre Intelligent Choreography Dataset and Network for 3D Dance Generation](https://arxiv.org/abs/2212.03741) \

 Tsinghua University, 7 Dec 2022

[Pretrained Diffusion Models for Unified Human Motion Synthesis](https://ofa-sys.github.io/MoFusion/) \

DAMO Academy, Alibaba Group, 6 Dec 2022

[EDGE: Editable Dance Generation From Music](https://arxiv.org/abs/2211.10658) \

Stanford University, 19 Nov 2022

[You Never Stop Dancing: Non-freezing Dance Generation via Bank-constrained Manifold Projection](https://openreview.net/forum?id=88ubVLwWvGD) \

MSRA, NeurIPS'22

[GroupDancer: Music to Multi-People Dance Synthesis with Style Collaboration](https://dl.acm.org/doi/abs/10.1145/3503161.3548090) \

Tsinghua University, ACMMM'22

[A Brand New Dance Partner: Music-Conditioned Pluralistic Dancing Controlled by Multiple Dance Genres](https://openaccess.thecvf.com/content/CVPR2022/papers/Kim_A_Brand_New_Dance_Partner_Music-Conditioned_Pluralistic_Dancing_Controlled_by_CVPR_2022_paper.pdf) \

Yonsei University, CVPR 2022, [[Code]](https://github.com/jw09191/MNET)

[Bailando: 3D Dance Generation by Actor-Critic GPT with Choreographic Memory](https://www.mmlab-ntu.com/project/bailando/index.html) \

NTU, CVPR 2022 (Oral), [[Code]](https://github.com/lisiyao21/Bailando)

[Dance Style Transfer with Cross-modal Transformer](https://arxiv.org/abs/2208.09406) \

KTH, 22 Aug 2022, [[Upcoming Code]](https://github.com/YIN95/cycledance-pytorch-lightning)

[Music-driven Dance Regeneration with Controllable Key Pose Constraints](https://arxiv.org/abs/2207.03682) \

Tencent, 8 July 2022

[AI Choreographer: Music Conditioned 3D Dance Generation with AIST++](https://google.github.io/aichoreographer/) \

USC, ICCV 2021, [[Code]](https://github.com/google-research/mint)

### Text-Driven motion generation

[ReMoDiffuse: Retrieval-Augmented Motion Diffusion Model](https://mingyuan-zhang.github.io/projects/ReMoDiffuse.html) \

NTU, CVPR'23, [[Code]](https://github.com/mingyuan-zhang/ReMoDiffuse)

[TEMOS: Generating diverse human motions from textual descriptions](mathis.petrovich.fr/temos/) \

ENPC, CVPR'23

[GestureDiffuCLIP: Gesture Diffusion Model with CLIP Latents](https://arxiv.org/abs/2303.14613) \

Peking University, CVPR'23

[Human Motion Diffusion as a Generative Prior](https://priormdm.github.io/priorMDM-page) \

Anonymous Authors, [[Code]](https://github.com/priorMDM/priorMDM)

[T2M-GPT: Generating Human Motion from Textual Descriptions with Discrete Representations](https://mael-zys.github.io/T2M-GPT/) \

Tencent AI Lab, 16 Jan 2023, [[Code]](https://github.com/Mael-zys/T2M-GPT)

[Modiff: Action-Conditioned 3D Motion Generation with Denoising Diffusion Probabilistic Models](https://arxiv.org/abs/2301.03949) \

Beihang University, 10 Jan 2023

[Executing your Commands via Motion Diffusion in Latent Space](https://chenxin.tech/mld/) \

Tencent, 8 Dec 2022, [[Code]](https://github.com/ChenFengYe/motion-latent-diffusion)

[MultiAct: Long-Term 3D Human Motion Generation from Multiple Action Labels](https://arxiv.org/abs/2212.05897) \

Seoul National University, AAAI 2023 Oral, [[Code]](https://github.com/TaeryungLee/MultiAct_RELEASE)

[MoFusion: A Framework for Denoising-Diffusion-based Motion Synthesis](https://vcai.mpi-inf.mpg.de/projects/MoFusion/) \

Max Planck Institute for Informatics, 8 Dec 2022

[Executing your Commands via Motion Diffusion in Latent Space](https://chenxin.tech/mld/) \

Tencent PCG, 8 Dec 2022, [[Upcoming Code]](https://github.com/ChenFengYe/motion-latent-diffusion)

[UDE: A Unified Driving Engine for Human Motion Generation](https://arxiv.org/pdf/2211.16016.pdf) \

Xiaobing Inc, 29 Nov 2022, [[Upcoming Code]](https://github.com/zixiangzhou916/UDE/)

[MotionBERT: Unified Pretraining for Human Motion Analysis](https://motionbert.github.io/) \

SenseTime Research, 12 Oct 2022, [[Code]](https://github.com/Walter0807/MotionBERT)

[Human Motion Diffusion Model](https://guytevet.github.io/mdm-page) \

Tel Aviv University, 3 Oct 2022, [[Code]](https://github.com/GuyTevet/motion-diffusion-model)

[FLAME: Free-form Language-based Motion Synthesis & Editing](https://arxiv.org/abs/2209.00349) \

Korea University, 1 Sep 2022

[MotionDiffuse: Text-Driven Human Motion Generation with Diffusion Model](https://mingyuan-zhang.github.io/projects/MotionDiffuse.html) \

NTU, 22 Aug 2022, [[Code]](https://github.com/mingyuan-zhang/MotionDiffuse)

[TEMOS: Generating diverse human motions from textual descriptions](https://mathis.petrovich.fr/temos/) \

MPI, ECCV 2022 (Oral), [[Code]](https://github.com/Mathux/TEMOS)

[GIMO: Gaze-Informed Human Motion Prediction in Context](https://geometry.stanford.edu/projects/gimo/) \

Stanford University, ECCV 2022, [[Code]](https://github.com/y-zheng18/GIMO)

[MotionCLIP: Exposing Human Motion Generation to CLIP Space](https://guytevet.github.io/motionclip-page/) \

Tel Aviv University, ECCV 2022, [[Code]](https://github.com/GuyTevet/MotionCLIP)

[Generating Diverse and Natural 3D Human Motions from Text](https://ericguo5513.github.io/text-to-motion/) \

University of Alberta, CVPR 2022, [[Code]](https://github.com/EricGuo5513/text-to-motion)

[AvatarCLIP: Zero-Shot Text-Driven Generation and Animation of 3D Avatars](https://hongfz16.github.io/projects/AvatarCLIP.html) \

NTU, SIGGRAPH 2022, [[Code]](https://github.com/hongfz16/AvatarCLIP)

[Text2Gestures: A Transformer-Based Network for Generating Emotive Body Gestures for Virtual Agents](https://arxiv.org/abs/2101.11101) \

University of Maryland,, VR 2021, [[Code]](https://github.com/UttaranB127/Text2Gestures)

### Audio-Driven motion generation

For more recent paper, you can find from [here](https://github.com/YunjinPark/awesome_talking_face_generation)

[Taming Diffusion Models for Audio-Driven Co-Speech Gesture Generation](https://github.com/Advocate99/DiffGesture) \

NTU, CVPR'23, [[Code]](https://github.com/Advocate99/DiffGesture)

[GeneFace: Generalized and High-Fidelity Audio-Driven 3D Talking Face Synthesis](https://geneface.github.io/) \

Zhejiang University, ICLR'23, [[Code]](https://github.com/yerfor/GeneFace)

[DiffMotion: Speech-Driven Gesture Synthesis Using Denoising Diffusion Model](https://arxiv.org/abs/2301.10047) \

 Macau University of Science and Technolog, 24 Jan 2023

[DiffTalk: Crafting Diffusion Models for Generalized Talking Head Synthesis](https://arxiv.org/abs/2301.03786) \

Tsinghua University, 10 Jan 2023

[Diffused Heads: Diffusion Models Beat GANs on Talking-Face Generation](https://mstypulkowski.github.io/diffusedheads/) \

University of Wrocław, 6 Jan 2023, [[Incoming Code]](https://github.com/MStypulkowski/diffused-heads)

[Generating Holistic 3D Human Motion from Speech](https://talkshow.is.tue.mpg.de/) \

Max Planck Institute for Intelligent Systems, 8 Dev 2022

[Audio-Driven Co-Speech Gesture Video Generation](https://arxiv.org/abs/2212.02350) \

NTU, 5 Dec 2022

[Listen, denoise, action! Audio-driven motion synthesis with diffusion models](https://www.speech.kth.se/research/listen-denoise-action/) \

KTH Royal Institute of Technology, 17 Nov 2022

[ZeroEGGS: Zero-shot Example-based Gesture Generation from Speech](https://arxiv.org/abs/2209.07556) \

York University, 23 Sep 2022, [[Code]](https://github.com/ubisoft/ubisoft-laforge-ZeroEGGS)

[BEAT: A Large-Scale Semantic and Emotional Multi-Modal Dataset for Conversational Gestures Synthesis](https://pantomatrix.github.io/BEAT/) \

The University of Tokyo, ECCV 2022, [[Code]](https://github.com/PantoMatrix/BEAT)

[EAMM: One-Shot Emotional Talking Face via Audio-Based Emotion-Aware Motion Model](https://jixinya.github.io/projects/EAMM/)\

Nanjing University, SIGGRAPH 2022, [[Code]](https://github.com/jixinya/EAMM/)

[Learning Hierarchical Cross-Modal Association for Co-Speech Gesture Generation](https://openaccess.thecvf.com/content/CVPR2022/papers/Liu_Learning_Hierarchical_Cross-Modal_Association_for_Co-Speech_Gesture_Generation_CVPR_2022_paper.pdf) \

The Chinese University of Hong Kong, CVPR 2022, [[Code]](https://github.com/alvinliu0/HA2G)

[SEEG: Semantic Energized Co-speech Gesture Generation](https://ffmpbgrnn.github.io/publications/pdf/seeg.pdf) \

Alibaba DAMO Academy, CVPR 2022, [[Code]](https://github.com/akira-l/SEEG)

[FaceFormer: Speech-Driven 3D Facial Animation with Transformers](https://evelynfan.github.io/audio2face/) \

The University of Hong Kong, CVPR 2022, [[Code]](https://github.com/EvelynFan/FaceFormer)

[Freeform Body Motion Generation from Speech](https://arxiv.org/abs/2203.02291) \

JD AI Research, 4 Mar 2022, [[Code]](https://github.com/TheTempAccount/Co-Speech-Motion-Generation)

[Audio2Gestures: Generating Diverse Gestures from Speech Audio with Conditional Variational Autoencoders](https://jingli513.github.io/audio2gestures/) \

Tencent AI Lab, ICCV 2021, [[Code]](https://github.com/JingLi513/Audio2Gestures)

[Learning Speech-driven 3D Conversational Gestures from Video](https://arxiv.org/abs/2102.06837) \

Max Planck Institute for Informatics, IVA 2021, [[Code]](http://gvv.mpi-inf.mpg.de/projects/3d_speech_driven_gesture/)

[Learning Individual Styles of Conversational Gesture](https://openaccess.thecvf.com/content_CVPR_2019/papers/Ginosar_Learning_Individual_Styles_of_Conversational_Gesture_CVPR_2019_paper.pdf) \

UC Berkeley, CVPR 2019, [[Code]](https://github.com/amirbar/speech2gesture)

### Human motion prediction

For more recent more, you can find from [here](https://github.com/aras62/vision-based-prediction/blob/master/papers/motion_papers.md)

[InterDiff: Generating 3D Human-Object Interactions with Physics-Informed Diffusion](https://sirui-xu.github.io/InterDiff/)\

UIUC, ICCV 2023, [[Code]](https://github.com/Sirui-Xu/InterDiff)

[Stochastic Multi-Person 3D Motion Forecasting](https://sirui-xu.github.io/DuMMF/)\

UIUC, ICLR 2023 (Spotlight), [[Code]](https://github.com/Sirui-Xu/DuMMF)

[HumanMAC: Masked Motion Completion for Human Motion Prediction](https://lhchen.top/Human-MAC/)\

Tsinghua University, ICCV 2023, [[Code]](https://github.com/LinghaoChan/HumanMAC)

[BeLFusion: Latent Diffusion for Behavior-Driven Human Motion Prediction](https://barquerogerman.github.io/BeLFusion/) \

University of Barcelona, 25 Nov 2022, [[Upcoming Code]](https://github.com/BarqueroGerman/BeLFusion)

[Diverse Human Motion Prediction Guided by Multi-Level Spatial-Temporal Anchors](https://sirui-xu.github.io/STARS/)\

UIUC, ECCV 2022 (Oral), [[Code]](https://github.com/Sirui-Xu/STARS)

[PoseGPT: Quantization-based 3D Human Motion Generation and Forecasting](https://europe.naverlabs.com/research/computer-vision/posegpt/) \

NAVER LABS, ECCV'2022, [[Code]](https://github.com/naver/PoseGPT)

[NeMF: Neural Motion Fields for Kinematic Animation](https://cs.yale.edu/homes/che/projects/nemf/) \

Yale University, NeurIPS 2022 (Spotlight), [[Code]](https://github.com/c-he/NeMF)

[Multi-Person Extreme Motion Prediction](https://openaccess.thecvf.com/content/CVPR2022/papers/Guo_Multi-Person_Extreme_Motion_Prediction_CVPR_2022_paper.pdf) \

Inria University, CVPR 2022, [[Code]](https://github.com/GUO-W/MultiMotion)

[MotionMixer: MLP-based 3D Human Body Pose Forecasting](https://arxiv.org/abs/2207.00499) \

Mercedes-Benz, IJCAI 2022 (Oral), [[Code]](https://github.com/MotionMLP/MotionMixer)

[Multi-Person 3D Motion Prediction with Multi-Range Transformers](https://arxiv.org/abs/2111.12073) \

UCSD, NeurIPS 2021

### Motion Applications

[MIME: Human-Aware 3D Scene Generation](https://mime.is.tue.mpg.de/) \

MPI

[Scene Synthesis from Human Motion](https://lijiaman.github.io/projects/summon/) \

Stanford University, SIGGRAPH Asia 2022, [[Code]](https://github.com/onestarYX/summon)

[TEACH: Temporal Action Compositions for 3D Humans](https://teach.is.tue.mpg.de/) \

MPI, 3DV 2022, [[Code]](https://github.com/athn-nik/teach)

[Motion In-betweening via Two-stage Transformers](http://kunzhou.net/2022/motion-siga22.pdf) \

Zhejiang University, SIGGRAPH Asia 2022

[Skeleton2Humanoid: Animating Simulated Characters for Physically-plausible Motion In-betweening](https://dl.acm.org/doi/abs/10.1145/3503161.3548093) \

Shanghai Jiaotong University, ACMMM 2022, [[Upcoming Code]](https://github.com/michaelliyunhao/Skeleton2Humanoid)

[Conditional Motion In-betweening](https://arxiv.org/abs/2202.04307) \

Korea University, 6 Oct 2022, [[Code]](https://github.com/jihoonerd/Conditional-Motion-In-Betweening)

[SkeletonMAE: Spatial-Temporal Masked Autoencoders for Self-supervised Skeleton Action Recognition](https://arxiv.org/abs/2209.02399) \

University of North Carolina, 1 Sep 2022

[A Unified Framework for Real Time Motion Completion](https://ojs.aaai.org/index.php/AAAI/article/view/20368) \

NetEase Games AI Lab, AAAI 2022

[Transformer based Motion In-betweening](https://openaccess.thecvf.com/content/ACCV2022W/TCV/papers/Sridhar_Transformer_Based_Motion_In-Betweening_ACCVW_2022_paper.pdf) \

National Institute of Technology - Tiruchirappalli, ACCV 2022 Workshop, [[Code]](https://github.com/Pavi114/motion-completion-using-transformers)

[Generative Tweening: Long-term Inbetweening of 3D Human Motions](https://zhouyisjtu.github.io/project_tweening/GenerativeTweening.html) \

Adobe Research, 28 May 2020

### Text-Image Generation

For more recent paper, you can find from [here](https://github.com/heejkoo/Awesome-Diffusion-Models#text-to-image)

[Adding Conditional Control to Text-to-Image Diffusion Models](https://github.com/lllyasviel/ControlNet) \

Stanford, Feb 2023

[SpaText: Spatio-Textual Representation for Controllable Image Generation](https://omriavrahami.com/spatext/) \

Meta AI (FAIR), 25 Nov 2022

[Sketch-Guided Text-to-Image Diffusion Models](https://arxiv.org/pdf/2211.13752.pdf) \

Google Research, 24 Nov 2022

[Make-A-Story: Visual Memory Conditioned Consistent Story Generation](https://arxiv.org/abs/2211.13319) \

University of British Columbia, 23 Nov 2022

[Synthesizing Coherent Story with Auto-Regressive Latent Diffusion Models](https://arxiv.org/pdf/2211.10950.pdf) \

University of Waterloo, 20 Nov 2022, [[Upcoming Code]](https://github.com/Flash-321/ARLDM)

[InstructPix2Pix: Learning to Follow Image Editing Instructions](https://arxiv.org/abs/2211.09800) \

UC Berkeley, 17 Nov 2022

[Null-text Inversion for Editing Real Images using Guided Diffusion Models](https://arxiv.org/abs/2211.09794) \

Google Research, 17 Nov 2022

[HumanDiffusion: a Coarse-to-Fine Alignment Diffusion Framework for Controllable Text-Driven Person Image Generation](https://arxiv.org/abs/2211.06235) \

University of Chinese Academy of Sciences, 11 Nov 2022

[Imagic: Text-Based Real Image Editing with Diffusion Models](https://imagic-editing.github.io/) \

Google Research, 17 Oct 2022

[Self-Guided Diffusion Models](https://arxiv.org/abs/2210.06462) \

University of Amsterdam, 12 Oct 2022

[On Distillation of Guided Diffusion Models](https://arxiv.org/abs/2210.03142) \

Stanford University, NeurIPS 2022 Workshop, 6 Oct 2022

[DreamBooth: Fine Tuning Text-to-Image Diffusion Models for Subject-Driven Generation](https://dreambooth.github.io/) \

Google Research, 25 Aug 2022, [[Code]](https://github.com/XavierXiao/Dreambooth-Stable-Diffusion)

[Prompt-to-Prompt Image Editing with Cross Attention Control](https://arxiv.org/abs/2208.01626) \

Google Research, 2 Aug 2022, [[Code]](https://github.com/bloc97/CrossAttentionControl)

[Improved Vector Quantized Diffusion Models](https://arxiv.org/abs/2205.16007) \

University of Science and Technology of China, 31 May 2022, [[Code]](https://github.com/cientgu/VQ-Diffusion)

[Make-A-Scene: Scene-Based Text-to-Image Generation with Human Priors](https://arxiv.org/pdf/2203.13131.pdf) \

Meta AI Research, 24 Mar 2022

[Diffusion Autoencoders: Toward a Meaningful and Decodable Representation](https://diff-ae.github.io/) \

Vidyasirimedhi Institute of Science and Technology, CVPR 2022 (Oral), [[Code]](https://github.com/phizaz/diffae)

[Vector Quantized Diffusion Model for Text-to-Image Synthesis](https://openaccess.thecvf.com/content/CVPR2022/papers/Gu_Vector_Quantized_Diffusion_Model_for_Text-to-Image_Synthesis_CVPR_2022_paper.pdf) \

University of Science and Technology of China, CVPR 2022, [[Code]](https://github.com/cientgu/VQ-Diffusion)

[High-Resolution Image Synthesis with Latent Diffusion Models](https://openaccess.thecvf.com/content/CVPR2022/papers/Rombach_High-Resolution_Image_Synthesis_With_Latent_Diffusion_Models_CVPR_2022_paper.pdf) \

Runway ML, CVPR 2022, [[Code]](https://github.com/CompVis/latent-diffusion)

### Text-Video Generation

[TI2V-Zero: Zero-Shot Image Conditioning for Text-to-Video Diffusion Models](https://arxiv.org/pdf/2404.16306) \

Penn State University, CVPR 2024, [[Code]](https://github.com/merlresearch/TI2V-Zero)

[Conditional Image-to-Video Generation with Latent Flow Diffusion Models](https://arxiv.org/pdf/2303.13744) \

Penn State University, CVPR 2023, [[Code]](https://github.com/nihaomiao/CVPR2023_LFDM)

[Text-To-4D Dynamic Scene Generation](https://make-a-video3d.github.io/) \

Meta AI, 2023, [[Code]](https://github.com/Make-A-Video3D/Make-A-Video3D.github.io)

[Structure and Content-Guided Video Synthesis with Diffusion Models](https://research.runwayml.com/gen1) \

Runway, 6 Feb 2023

[Latent Video Diffusion Models for High-Fidelity Video Generation with Arbitrary Lengths](https://yingqinghe.github.io/LVDM/) \

The Hong Kong University of Science and Technology, 23 Nov 2022, [[Upcoming Code]](https://github.com/YingqingHe/LVDM)

[MagicVideo: Efficient Video Generation With Latent Diffusion Models](https://magicvideo.github.io/) \

ByteDance Inc, 20 Nov 2022

[Text2LIVE: Text-Driven Layered Image and Video Editing](https://text2live.github.io/) \

NVIDIA Research, ECCV 2022 (Oral), [[Code]](https://github.com/omerbt/Text2LIVE)

### Text-3D Image Generation

[Point-E: A System for Generating 3D Point Clouds from Complex Prompts](https://arxiv.org/abs/2212.08751) \

OpenAI, 16 Dec 2022

[DreamFusion: Text-to-3D using 2D Diffusion](https://dreamfusion3d.github.io/) \

Google Research, 29 Sep 2022