Video
updated
Motion-I2V: Consistent and Controllable Image-to-Video Generation with
Explicit Motion Modeling
Paper
• 2401.15977
• Published
• 39
Lumiere: A Space-Time Diffusion Model for Video Generation
Paper
• 2401.12945
• Published
• 87
AnimateDiff: Animate Your Personalized Text-to-Image Diffusion Models
without Specific Tuning
Paper
• 2307.04725
• Published
• 65
Boximator: Generating Rich and Controllable Motions for Video Synthesis
Paper
• 2402.01566
• Published
• 27
ConsistI2V: Enhancing Visual Consistency for Image-to-Video Generation
Paper
• 2402.04324
• Published
• 26
MagicDance: Realistic Human Dance Video Generation with Motions & Facial
Expressions Transfer
Paper
• 2311.12052
• Published
• 32
Magic-Me: Identity-Specific Video Customized Diffusion
Paper
• 2402.09368
• Published
• 31
Direct-a-Video: Customized Video Generation with User-Directed Camera
Movement and Object Motion
Paper
• 2402.03162
• Published
• 19
AnimateLCM: Accelerating the Animation of Personalized Diffusion Models
and Adapters with Decoupled Consistency Learning
Paper
• 2402.00769
• Published
• 22
I2V-Adapter: A General Image-to-Video Adapter for Video Diffusion Models
Paper
• 2312.16693
• Published
• 14
DreamVideo: Composing Your Dream Videos with Customized Subject and
Motion
Paper
• 2312.04433
• Published
• 10
MotionCtrl: A Unified and Flexible Motion Controller for Video
Generation
Paper
• 2312.03641
• Published
• 22
AnimateAnything: Fine-Grained Open Domain Image Animation with Motion
Guidance
Paper
• 2311.12886
• Published
VideoComposer: Compositional Video Synthesis with Motion Controllability
Paper
• 2306.02018
• Published
• 3
Media2Face: Co-speech Facial Animation Generation With Multi-Modality
Guidance
Paper
• 2401.15687
• Published
• 24
Customizing Motion in Text-to-Video Diffusion Models
Paper
• 2312.04966
• Published
• 11
World Model on Million-Length Video And Language With RingAttention
Paper
• 2402.08268
• Published
• 40
Animate Anyone: Consistent and Controllable Image-to-Video Synthesis for
Character Animation
Paper
• 2311.17117
• Published
• 6
Genie: Generative Interactive Environments
Paper
• 2402.15391
• Published
• 72
EMO: Emote Portrait Alive - Generating Expressive Portrait Videos with
Audio2Video Diffusion Model under Weak Conditions
Paper
• 2402.17485
• Published
• 194
Sora: A Review on Background, Technology, Limitations, and Opportunities
of Large Vision Models
Paper
• 2402.17177
• Published
• 88
AnimateDiff-Lightning: Cross-Model Diffusion Distillation
Paper
• 2403.12706
• Published
• 18
SV3D: Novel Multi-view Synthesis and 3D Generation from a Single Image
using Latent Video Diffusion
Paper
• 2403.12008
• Published
• 20
V3D: Video Diffusion Models are Effective 3D Generators
Paper
• 2403.06738
• Published
• 30
DynamiCrafter: Animating Open-domain Images with Video Diffusion Priors
Paper
• 2310.12190
• Published
• 13
Mora: Enabling Generalist Video Generation via A Multi-Agent Framework
Paper
• 2403.13248
• Published
• 78
CameraCtrl: Enabling Camera Control for Text-to-Video Generation
Paper
• 2404.02101
• Published
• 24
Ctrl-Adapter: An Efficient and Versatile Framework for Adapting Diverse
Controls to Any Diffusion Model
Paper
• 2404.09967
• Published
• 21
PhysDreamer: Physics-Based Interaction with 3D Objects via Video
Generation
Paper
• 2404.13026
• Published
• 24
StoryDiffusion: Consistent Self-Attention for Long-Range Image and Video
Generation
Paper
• 2405.01434
• Published
• 56
MotionLCM: Real-time Controllable Motion Generation via Latent
Consistency Model
Paper
• 2404.19759
• Published
• 27
MagicVideo-V2: Multi-Stage High-Aesthetic Video Generation
Paper
• 2401.04468
• Published
• 49
Make Pixels Dance: High-Dynamic Video Generation
Paper
• 2311.10982
• Published
• 68
Emu3: Next-Token Prediction is All You Need
Paper
• 2409.18869
• Published
• 97
VideoJAM: Joint Appearance-Motion Representations for Enhanced Motion
Generation in Video Models
Paper
• 2502.02492
• Published
• 66
Goku: Flow Based Video Generative Foundation Models
Paper
• 2502.04896
• Published
• 106
Intuitive physics understanding emerges from self-supervised pretraining
on natural videos
Paper
• 2502.11831
• Published
• 20