ReadPapers
1.
Introduction
2.
Locomotion 技术洞察
3.
AMP: Adversarial Motion Priors for Stylized Physics-Based Character Control
4.
ASE: Large-Scale Reusable Adversarial Skill Embeddings for Physically Simulated Characters
5.
Feature-Based Locomotion Controllers
6.
DeepMimic: Example-Guided Deep Reinforcement Learning of Physics-Based Character Skills
7.
ControlVAE: Model-Based Learning of Generative Controllers for Physics-Based Characters
8.
Trace and Pace: Controllable Pedestrian Animation via Guided Trajectory Diffusion
9.
UniPhys Unified Planner and Controller with Diffusion for Flexible
10.
Diffuse-CLoC: Guided Diffusion for Physics-based Character Look-ahead
11.
PDP: Physics-Based Character Animation via Diffusion Policy
12.
DiffuseLoco: Real-Time Legged Locomotion Control with Diffusion from Offline Datasets
13.
Perpetual Humanoid Control for Real-time Simulated Avatars
14.
Calm: Conditional Adversarial Latent Models for Directable Virtual Characters
15.
Universal humanoid motion representations for physics-based control
16.
DReCon: data-driven responsive control of physics-based characters
17.
PARC: Physics-based Augmentation with Reinforcement Learning for Character Controllers
18.
CLOSD: CLOSING THE LOOP BETWEEN SIMULATION AND DIFFUSION FOR MULTI-TASK CHARACTER CONTROL
19.
MotionPersona: Characteristics-aware Locomotion Control
20.
Diffuse-CLoC Guided Diffusion for Physics-based Character Look-ahead
21.
Gait-Conditioned Reinforcement Learning with Multi-Phase Curriculum for Humanoid Locomotion
22.
UniPhys: Unified Planner and Controller with Diffusion for Flexible
23.
Maskedmimic: Unified physics-based character control through masked motion
24.
Regional Time Stepping for SPH
25.
FreeGave: 3D Physics Learning from Dynamic Videos by Gaussian Velocity
26.
Physics-informed neural networks: A deep learning framework for solving forward and inverse problems involving nonlinear partial differential equations
27.
ParticleGS: Particle-Based Dynamics Modeling of 3D Gaussians for Prior-free Motion Extrapolation
28.
Animate3d: Animating any 3d model with multi-view video diffusion
29.
Particle-Grid Neural Dynamics for Learning Deformable Object Models from RGB-D Videos
30.
HAIF-GS: Hierarchical and Induced Flow-Guided Gaussian Splatting for Dynamic Scene
31.
PIG: Physically-based Multi-Material Interaction with 3D Gaussians
32.
EnliveningGS: Active Locomotion of 3DGS
33.
SplineGS: Learning Smooth Trajectories in Gaussian Splatting for Dynamic Scene Reconstruction
34.
PAMD: Plausibility-Aware Motion Diffusion Model for Long Dance Generation
35.
PMG: Progressive Motion Generation via Sparse Anchor Postures Curriculum Learning
36.
LengthAware Motion Synthesis via Latent Diffusion
37.
IKMo: Image-Keyframed Motion Generation with Trajectory-Pose Conditioned Motion Diffusion Model
38.
UniMoGen: Universal Motion Generation
39.
AMD: Anatomical Motion Diffusion with Interpretable Motion Decomposition and Fusion
40.
Flame: Free-form language-based motion synthesis & editing
41.
Human Motion Diffusion as a Generative Prior
42.
Text-driven Human Motion Generation with Motion Masked Diffusion Model
43.
ReMoDiffuse: RetrievalAugmented Motion Diffusion Model
44.
MotionLCM: Real-time Controllable Motion Generation via Latent Consistency Model
45.
ReAlign: Bilingual Text-to-Motion Generation via Step-Aware Reward-Guided Alignment
46.
Absolute Coordinates Make Motion Generation Easy
47.
Seamless Human Motion Composition with Blended Positional Encodings
48.
FineMoGen: Fine-Grained Spatio-Temporal Motion Generation and Editing
49.
Fg-T2M: Fine-Grained Text-Driven Human Motion Generation via Diffusion Model
50.
Make-An-Animation: Large-Scale Text-conditional 3D Human Motion Generation
51.
StableMoFusion: Towards Robust and Efficient Diffusion-based Motion Generation Framework
52.
EMDM: Efficient Motion Diffusion Model for Fast and High-Quality Motion Generation
53.
Motion Mamba: Efficient and Long Sequence Motion Generation
54.
M2D2M: Multi-Motion Generation from Text with Discrete Diffusion Models
55.
T2LM: Long-Term 3D Human Motion Generation from Multiple Sentences
56.
AttT2M:Text-Driven Human Motion Generation with Multi-Perspective Attention Mechanism
57.
BAD: Bidirectional Auto-Regressive Diffusion for Text-to-Motion Generation
58.
MMM: Generative Masked Motion Model
59.
Priority-Centric Human Motion Generation in Discrete Latent Space
60.
AvatarGPT: All-in-One Framework for Motion Understanding, Planning, Generation and Beyond
61.
MotionGPT: Human Motion as a Foreign Language
62.
Action-GPT: Leveraging Large-scale Language Models for Improved and Generalized Action Generation
63.
PoseGPT: Quantization-based 3D Human Motion Generation and Forecasting
64.
Incorporating Physics Principles for Precise Human Motion Prediction
65.
PIMNet: Physics-infused Neural Network for Human Motion Prediction
66.
PhysDiff: Physics-Guided Human Motion Diffusion Model
67.
NRDF: Neural Riemannian Distance Fields for Learning Articulated Pose Priors
68.
Riemannian Motion Generation: A Unified Framework for Human Motion Representation and Generation via Riemannian Flow Matching
69.
Pose-NDF: Modeling Human Pose Manifolds with Neural Distance Fields
70.
Geometric Neural Distance Fields for Learning Human Motion Priors
71.
Character Controllers Using Motion VAEs
72.
Improving Human Motion Plausibility with Body Momentum
73.
MoGlow: Probabilistic and controllable motion synthesis using normalising flows
74.
Modi: Unconditional motion synthesis from diverse data
75.
MotionDiffuse: Text-Driven Human Motion Generation with Diffusion Model
76.
A deep learning framework for character motion synthesis and editing
77.
Multi-Object Sketch Animation with Grouping and Motion Trajectory Priors
78.
TRACE: Learning 3D Gaussian Physical Dynamics from Multi-view Videos
79.
X-MoGen: Unified Motion Generation across Humans and Animals
80.
Gaussian Variation Field Diffusion for High-fidelity Video-to-4D Synthesis
81.
MotionShot: Adaptive Motion Transfer across Arbitrary Objects for Text-to-Video Generation
82.
Drop: Dynamics responses from human motion prior and projective dynamics
83.
POMP: Physics-constrainable Motion Generative Model through Phase Manifolds
84.
Dreamgaussian4d: Generative 4d gaussian splatting
85.
Drive Any Mesh: 4D Latent Diffusion for Mesh Deformation from Video
86.
AnimateAnyMesh: A Feed-Forward 4D Foundation Model for Text-Driven Universal Mesh Animation
87.
ReVision: High-Quality, Low-Cost Video Generation with Explicit 3D Physics Modeling for Complex Motion and Interaction
88.
Text2Video-Zero: Text-to-Image Diffusion Models are Zero-Shot Video Generators
89.
Force Prompting: Video Generation Models Can Learn and Generalize Physics-based Control Signals
90.
Think Before You Diffuse: LLMs-Guided Physics-Aware Video Generation
91.
Generating time-consistent dynamics with discriminator-guided image diffusion models
92.
GENMO:AGENeralist Model for Human MOtion
93.
HGM3: HIERARCHICAL GENERATIVE MASKED MOTION MODELING WITH HARD TOKEN MINING
94.
Towards Robust and Controllable Text-to-Motion via Masked Autoregressive Diffusion
95.
MoCLIP: Motion-Aware Fine-Tuning and Distillation of CLIP for Human Motion Generation
96.
FinePhys: Fine-grained Human Action Generation by Explicitly Incorporating Physical Laws for Effective Skeletal Guidance
97.
VideoSwap: Customized Video Subject Swapping with Interactive Semantic Point Correspondence
98.
DragAnything: Motion Control for Anything using Entity Representation
99.
PhysAnimator: Physics-Guided Generative Cartoon Animation
100.
SOAP: Style-Omniscient Animatable Portraits
101.
Neural Discrete Representation Learning
102.
TSTMotion: Training-free Scene-aware Text-to-motion Generation
103.
Deterministic-to-Stochastic Diverse Latent Feature Mapping for Human Motion Synthesis
104.
A lip sync expert is all you need for speech to lip generation in the wild
105.
MUSETALK: REAL-TIME HIGH QUALITY LIP SYN-CHRONIZATION WITH LATENT SPACE INPAINTING
106.
LatentSync: Audio Conditioned Latent Diffusion Models for Lip Sync
107.
T2m-gpt: Generating human motion from textual descriptions with discrete representations
108.
Motiongpt: Finetuned llms are general-purpose motion generators
109.
Guided Motion Diffusion for Controllable Human Motion Synthesis
110.
OmniControl: Control Any Joint at Any Time for Human Motion Generation
111.
Learning Long-form Video Prior via Generative Pre-Training
112.
Instant Neural Graphics Primitives with a Multiresolution Hash Encoding
113.
Magic3D: High-Resolution Text-to-3D Content Creation
114.
CogVideo: Large-scale Pretraining for Text-to-Video Generation via Transformers
115.
One-Minute Video Generation with Test-Time Training
116.
Key-Locked Rank One Editing for Text-to-Image Personalization
117.
MARCHING CUBES: A HIGH RESOLUTION 3D SURFACE CONSTRUCTION ALGORITHM
118.
Plug-and-Play Diffusion Features for Text-Driven Image-to-Image Translation
119.
NULL-text Inversion for Editing Real Images Using Guided Diffusion Models
120.
simple diffusion: End-to-end diffusion for high resolution images
121.
One Transformer Fits All Distributions in Multi-Modal Diffusion at Scale
122.
Scalable Diffusion Models with Transformers
123.
All are Worth Words: a ViT Backbone for Score-based Diffusion Models
124.
An image is worth 16x16 words: Transformers for image recognition at scale
125.
eDiff-I: Text-to-Image Diffusion Models with an Ensemble of Expert Denoisers
126.
Photorealistic text-to-image diffusion models with deep language understanding||Imagen
127.
DreamFusion: Text-to-3D using 2D Diffusion
128.
GLIGEN: Open-Set Grounded Text-to-Image Generation
129.
Adding Conditional Control to Text-to-Image Diffusion Models
130.
T2I-Adapter: Learning Adapters to Dig out More Controllable Ability for Text-to-Image Diffusion Models
131.
Multi-Concept Customization of Text-to-Image Diffusion
132.
An Image is Worth One Word: Personalizing Text-to-Image Generation using Textual Inversion
133.
DreamBooth: Fine Tuning Text-to-Image Diffusion Models for Subject-Driven Generation
134.
VisorGPT: Learning Visual Prior via Generative Pre-Training
135.
NUWA-XL: Diffusion over Diffusion for eXtremely Long Video Generation
136.
AnimateDiff: Animate Your Personalized Text-to-Image Diffusion Models without Specific Tuning
137.
ModelScope Text-to-Video Technical Report
138.
Show-1: Marrying Pixel and Latent Diffusion Models for Text-to-Video Generation
139.
Make-A-Video: Text-to-Video Generation without Text-Video Data
140.
Video Diffusion Models
141.
Learning Transferable Visual Models From Natural Language Supervision
142.
Implicit Warping for Animation with Image Sets
143.
Mix-of-Show: Decentralized Low-Rank Adaptation for Multi-Concept Customization of Diffusion Models
144.
Motion-Conditioned Diffusion Model for Controllable Video Synthesis
145.
Stable Video Diffusion: Scaling Latent Video Diffusion Models to Large Datasets
146.
UniAnimate: Taming Unified Video Diffusion Models for Consistent Human Image Animation
147.
Align your Latents: High-Resolution Video Synthesis with Latent Diffusion Models
148.
Puppet-Master: Scaling Interactive Video Generation as a Motion Prior for Part-Level Dynamics
149.
A Recipe for Scaling up Text-to-Video Generation
150.
High-Resolution Image Synthesis with Latent Diffusion Models
151.
Motion-I2V: Consistent and Controllable Image-to-Video Generation with Explicit Motion Modeling
152.
数据集：HumanVid
153.
HumanVid: Demystifying Training Data for Camera-controllable Human Image Animation
154.
StoryDiffusion: Consistent Self-Attention for Long-Range Image and Video Generation
155.
数据集：Zoo-300K
156.
Motion Avatar: Generate Human and Animal Avatars with Arbitrary Motion
157.
LORA: LOW-RANK ADAPTATION OF LARGE LAN-GUAGE MODELS
158.
TCAN: Animating Human Images with Temporally Consistent Pose Guidance using Diffusion Models
159.
GaussianAvatar: Towards Realistic Human Avatar Modeling from a Single Video via Animatable 3D Gaussians
160.
MagicPony: Learning Articulated 3D Animals in the Wild
161.
Splatter a Video: Video Gaussian Representation for Versatile Processing
162.
数据集：Dynamic Furry Animal Dataset
163.
Artemis: Articulated Neural Pets with Appearance and Motion Synthesis
164.
SMPLer: Taming Transformers for Monocular 3D Human Shape and Pose Estimation
165.
CAT3D: Create Anything in 3D with Multi-View Diffusion Models
166.
PACER+: On-Demand Pedestrian Animation Controller in Driving Scenarios
167.
Humans in 4D: Reconstructing and Tracking Humans with Transformers
168.
Learning Human Motion from Monocular Videos via Cross-Modal Manifold Alignment
169.
PhysPT: Physics-aware Pretrained Transformer for Estimating Human Dynamics from Monocular Videos
170.
Imagic: Text-Based Real Image Editing with Diffusion Models
171.
DiffEdit: Diffusion-based semantic image editing with mask guidance
172.
Dual diffusion implicit bridges for image-to-image translation
173.
SDEdit: Guided Image Synthesis and Editing with Stochastic Differential Equations
174.
Prompt-to-Prompt Image Editing with Cross-Attention Control
175.
WANDR: Intention-guided Human Motion Generation
176.
TRAM: Global Trajectory and Motion of 3D Humans from in-the-wild Videos
177.
3D Gaussian Splatting for Real-Time Radiance Field Rendering
178.
Decoupling Human and Camera Motion from Videos in the Wild
179.
HMP: Hand Motion Priors for Pose and Shape Estimation from Video
180.
HuMoR: 3D Human Motion Model for Robust Pose Estimation
181.
Co-Evolution of Pose and Mesh for 3D Human Body Estimation from Video
182.
Global-to-Local Modeling for Video-based 3D Human Pose and Shape Estimation
183.
WHAM: Reconstructing World-grounded Humans with Accurate 3D Motion
184.
Tackling the Generative Learning Trilemma with Denoising Diffusion GANs
185.
Elucidating the Design Space of Diffusion-Based Generative Models
186.
SCORE-BASED GENERATIVE MODELING THROUGHSTOCHASTIC DIFFERENTIAL EQUATIONS
187.
Consistency Models
188.
Classifier-Free Diffusion Guidance
189.
Cascaded Diffusion Models for High Fidelity Image Generation
190.
LEARNING ENERGY-BASED MODELS BY DIFFUSIONRECOVERY LIKELIHOOD
191.
On Distillation of Guided Diffusion Models
192.
Denoising Diffusion Implicit Models
193.
PROGRESSIVE DISTILLATION FOR FAST SAMPLING OF DIFFUSION MODELS
194.
Instruct-NeRF2NeRF: Editing 3D Scenes with Instructions
195.
ControlVideo: Training-free Controllable Text-to-Video Generation
196.
Pix2Video: Video Editing using Image Diffusion
197.
Structure and Content-Guided Video Synthesis with Diffusion Models
198.
MagicAnimate: Temporally Consistent Human Image Animation using Diffusion Model
199.
MotionDirector: Motion Customization of Text-to-Video Diffusion Models
200.
Dreamix: Video Diffusion Models are General Video Editors
201.
Tune-A-Video: One-Shot Tuning of Image Diffusion Models for Text-to-Video Generation
202.
TokenFlow: Consistent Diffusion Features for Consistent Video Editing
203.
DynVideo-E: Harnessing Dynamic NeRF for Large-Scale Motion- and View-Change Human-Centric Video Editing
204.
Content Deformation Fields for Temporally Consistent Video Processing
205.
PFNN: Phase-Functioned Neural Networks
206.
Recurrent Transition Networks for Character Locomotion
207.
Real-Time Style Modelling of Human Locomotion
208.
Motion In-Betweening with Phase Manifolds
209.
Mode-Adaptive Neural Networks for Quadruped Motion Control
210.
Few-shot Learning of Homogeneous Human Locomotion Styles
211.
Learning predict-and-simulate policies from unorganized human motion data
212.
Local Motion Phases for Learning Multi-Contact Character Movements
213.
Interactive Control of Diverse Complex Characters with Neural Networks
214.
Accelerated Auto-regressive Motion Diffusion Model
215.
DARTControl: A Diffusion-based Autoregressive Motion Model for Real-time Text-driven Motion Control
216.
Interactive Character Control with Auto-Regressive Motion Diffusion Models
217.
Taming Diffusion Probabilistic Models for Character Control
218.
Learned Motion Matching
219.
MOCHA: Real-Time Motion Characterization via Context Matching
220.
DeepLoco: Dynamic Locomotion Skills Using Hierarchical Deep Reinforcement Learning
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ReadPapers
数据集：Zoo-300K
该数据集包含约 300,000 对文本描述和跨越 65 个不同动物类别的相应动物运动。
原始数据
Truebones Zoo [2] 数据集
合成数据
对原始数据的动作进行增强
人工标注
用表示动物和运动类别的文本标签进行注释
生成标注
reference
论文：
link
