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.
FluidNexus: 3D Fluid Reconstruction and Prediction from a Single Video
Toward Lightweight and Fast Decoders for Diffusion Models in Image and Video Generation
Rethinking Video Super-Resolution: Towards Diffusion-Based Methods without Motion Alignment
High-Quality Virtual Single-Viewpoint Surgical Video: Geometric Autocalibration of Multiple Cameras in Surgical Lights
DualDiff+: Dual-Branch Diffusion for High-Fidelity Video Generation with Reward Guidance
Rethinking Video Tokenization: A Conditioned Diffusion-based Approach
GEN3C: 3D-Informed World-Consistent Video Generation with Precise Camera Control
VideoUFO: A Million-Scale User-Focused Dataset for Text-to-Video Generation
Extrapolating and Decoupling Image-to-Video Generation Models: Motion Modeling is Easier Than You Think
HAIC: Improving Human Action Understanding and Generation with Better Captions for Multi-modal Large Language Models
Unified Video Action Model
C-Drag: Chain-of-Thought Driven Motion Controller for Video Generation
FlexiDiT: Your Diffusion Transformer Can Easily Generate High-Quality Samples with Less Compute
Mobius: Text to Seamless Looping Video Generation via Latent Shift
Online Pseudo-average Shifting Attention(PASA) for Robust Low-precision LLM Inference: Algorithms and Numerical Analysis
ASurvey: Spatiotemporal Consistency in Video Generation
SpargeAttention: Accurate and Training-free Sparse Attention Accelerating Any Model Inference
Diffusion Models for Tabular Data: Challenges, Current Progress, and Future Directions
VideoGrain: Modulating Space-Time Attention for Multi-grained Video Editing
X-Dancer: Expressive Music to Human Dance Video Generation
RIFLEx: A Free Lunch for Length Extrapolation in Video Diffusion Transformers
Designing Parameter and Compute Efficient Diffusion Transformers using Distillation
RelaCtrl: Relevance-Guided Efficient Control for Diffusion Transformers
Improving the Diffusability of Autoencoders
Hardware-Friendly Static Quantization Method for Video Diffusion Transformers
MALT Diffusion: Memory-Augmented Latent Transformers for Any-Length Video Generation
VidCapBench: A Comprehensive Benchmark of Video Captioning for Controllable Text-to-Video Generation
LLMPopcorn: An Empirical Study of LLMs as Assistants for Popular Micro-video Generation
Object-Centric Image to Video Generation with Language Guidance
DLFR-VAE: Dynamic Latent Frame Rate VAE for Video Generation
Phantom: Subject-consistent video generation via cross-modal alignment
MaskFlow: Discrete Flows For Flexible and Efficient Long Video Generation
RealCam-I2V: Real-World Image-to-Video Generation with Interactive Complex Camera Control
Step-Video-T2V Technical Report: The Practice, Challenges, and Future of Video Foundation Model
GEVRM: Goal-Expressive Video Generation Model For Robust Visual Manipulation
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