Papers with Code 아카이브
Video Generation
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<span style="color:grey; opacity: 0.6">( Various Video Generation Tasks. Gif credit: MaGViT )</span>
논문
이 태스크와 하위 분야의 관련 논문입니다. 실제 성능 비교는 평가 결과에서 확인하세요.
VideoMAR: Autoregressive Video Generatio with Continuous Tokens
Causally Steered Diffusion for Automated Video Counterfactual Generation
STAGE: A Stream-Centric Generative World Model for Long-Horizon Driving-Scene Simulation
UltraVideo: High-Quality UHD Video Dataset with Comprehensive Captions
iDiT-HOI: Inpainting-based Hand Object Interaction Reenactment via Video Diffusion Transformer
AniMaker: Automated Multi-Agent Animated Storytelling with MCTS-Driven Clip Generation
DreamActor-H1: High-Fidelity Human-Product Demonstration Video Generation via Motion-designed Diffusion Transformers
GigaVideo-1: Advancing Video Generation via Automatic Feedback with 4 GPU-Hours Fine-Tuning
M4V: Multi-Modal Mamba for Text-to-Video Generation
GenWorld: Towards Detecting AI-generated Real-world Simulation Videos
PlayerOne: Egocentric World Simulator
How Much To Guide: Revisiting Adaptive Guidance in Classifier-Free Guidance Text-to-Vision Diffusion Models
HunyuanVideo-HOMA: Generic Human-Object Interaction in Multimodal Driven Human Animation
Cosmos-Drive-Dreams: Scalable Synthetic Driving Data Generation with World Foundation Models
MagCache: Fast Video Generation with Magnitude-Aware Cache
FlagEvalMM: A Flexible Framework for Comprehensive Multimodal Model Evaluation
PolyVivid: Vivid Multi-Subject Video Generation with Cross-Modal Interaction and Enhancement
Generative Modeling of Weights: Generalization or Memorization?
Audio-Sync Video Generation with Multi-Stream Temporal Control
Self Forcing: Bridging the Train-Test Gap in Autoregressive Video Diffusion
Seeing Voices: Generating A-Roll Video from Audio with Mirage
From Generation to Generalization: Emergent Few-Shot Learning in Video Diffusion Models
Follow-Your-Creation: Empowering 4D Creation through Video Inpainting
FPSAttention: Training-Aware FP8 and Sparsity Co-Design for Fast Video Diffusion
DualX-VSR: Dual Axial Spatial$\times$Temporal Transformer for Real-World Video Super-Resolution without Motion Compensation
FEAT: Full-Dimensional Efficient Attention Transformer for Medical Video Generation
Astraea: A GPU-Oriented Token-wise Acceleration Framework for Video Diffusion Transformers
ContentV: Efficient Training of Video Generation Models with Limited Compute
FullDiT2: Efficient In-Context Conditioning for Video Diffusion Transformers
SViMo: Synchronized Diffusion for Video and Motion Generation in Hand-object Interaction Scenarios
ORV: 4D Occupancy-centric Robot Video Generation
TalkingMachines: Real-Time Audio-Driven FaceTime-Style Video via Autoregressive Diffusion Models
IllumiCraft: Unified Geometry and Illumination Diffusion for Controllable Video Generation
LongDWM: Cross-Granularity Distillation for Building a Long-Term Driving World Model
OmniV2V: Versatile Video Generation and Editing via Dynamic Content Manipulation
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.