Progressive Autoregressive Video Diffusion Models
Fuente:
arXiv
Guardado en:
| Autores principales: | Xie, Desai, Xu, Zhan, Hong, Yicong, Tan, Hao, Liu, Difan, Liu, Feng, Kaufman, Arie, Zhou, Yang |
|---|---|
| Formato: | Preprint |
| Publicado: |
2024
|
| Materias: | |
| Acceso en línea: | |
| Etiquetas: |
Agregar Etiqueta
Sin Etiquetas, Sea el primero en etiquetar este registro!
|
Ejemplares similares
Carve3D: Improving Multi-view Reconstruction Consistency for Diffusion Models with RL Finetuning
por: Xie, Desai, et al.
Publicado: (2023)
por: Xie, Desai, et al.
Publicado: (2023)
Rethinking Training Dynamics in Scale-wise Autoregressive Generation
por: Zhou, Gengze, et al.
Publicado: (2025)
por: Zhou, Gengze, et al.
Publicado: (2025)
LRM-Zero: Training Large Reconstruction Models with Synthesized Data
por: Xie, Desai, et al.
Publicado: (2024)
por: Xie, Desai, et al.
Publicado: (2024)
Pushing the Boundaries of State Space Models for Image and Video Generation
por: Hong, Yicong, et al.
Publicado: (2025)
por: Hong, Yicong, et al.
Publicado: (2025)
LRM: Large Reconstruction Model for Single Image to 3D
por: Hong, Yicong, et al.
Publicado: (2023)
por: Hong, Yicong, et al.
Publicado: (2023)
Unlearning Concepts from Text-to-Video Diffusion Models
por: Liu, Shiqi, et al.
Publicado: (2024)
por: Liu, Shiqi, et al.
Publicado: (2024)
Sparse Forcing: Native Trainable Sparse Attention for Real-time Autoregressive Diffusion Video Generation
por: Xu, Boxun, et al.
Publicado: (2026)
por: Xu, Boxun, et al.
Publicado: (2026)
BAgger: Backwards Aggregation for Mitigating Drift in Autoregressive Video Diffusion Models
por: Po, Ryan, et al.
Publicado: (2025)
por: Po, Ryan, et al.
Publicado: (2025)
Diffusion Transformer-to-Mamba Distillation for High-Resolution Image Generation
por: Yao, Yuan, et al.
Publicado: (2025)
por: Yao, Yuan, et al.
Publicado: (2025)
Accelerating Video Inverse Problem Solvers with Autoregressive Diffusion Models
por: Kwon, Taesung, et al.
Publicado: (2026)
por: Kwon, Taesung, et al.
Publicado: (2026)
Self Forcing: Bridging the Train-Test Gap in Autoregressive Video Diffusion
por: Huang, Xun, et al.
Publicado: (2025)
por: Huang, Xun, et al.
Publicado: (2025)
REGEN: Learning Compact Video Embedding with (Re-)Generative Decoder
por: Zhang, Yitian, et al.
Publicado: (2025)
por: Zhang, Yitian, et al.
Publicado: (2025)
Physics-Driven Spatiotemporal Modeling for AI-Generated Video Detection
por: Zhang, Shuhai, et al.
Publicado: (2025)
por: Zhang, Shuhai, et al.
Publicado: (2025)
Progressive Compression with Universally Quantized Diffusion Models
por: Yang, Yibo, et al.
Publicado: (2024)
por: Yang, Yibo, et al.
Publicado: (2024)
Radioactive Watermarks in Diffusion and Autoregressive Image Generative Models
por: Meintz, Michel, et al.
Publicado: (2025)
por: Meintz, Michel, et al.
Publicado: (2025)
Redefining Temporal Modeling in Video Diffusion: The Vectorized Timestep Approach
por: Liu, Yaofang, et al.
Publicado: (2024)
por: Liu, Yaofang, et al.
Publicado: (2024)
Inferring Dynamic Physical Properties from Video Foundation Models
por: Zhan, Guanqi, et al.
Publicado: (2025)
por: Zhan, Guanqi, et al.
Publicado: (2025)
SIDE: Surrogate Conditional Data Extraction from Diffusion Models
por: Chen, Yunhao, et al.
Publicado: (2024)
por: Chen, Yunhao, et al.
Publicado: (2024)
Attend Locally, Remember Linearly: Linear Attention as Cross-Frame Memory for Autoregressive Video Diffusion
por: Li, Kunyang, et al.
Publicado: (2026)
por: Li, Kunyang, et al.
Publicado: (2026)
Masked Autoencoders Are Effective Tokenizers for Diffusion Models
por: Chen, Hao, et al.
Publicado: (2025)
por: Chen, Hao, et al.
Publicado: (2025)
Zero-Shot Video Restoration and Enhancement Using Pre-Trained Image Diffusion Model
por: Cao, Cong, et al.
Publicado: (2024)
por: Cao, Cong, et al.
Publicado: (2024)
Condition Errors Refinement in Autoregressive Image Generation with Diffusion Loss
por: Zhou, Yucheng, et al.
Publicado: (2026)
por: Zhou, Yucheng, et al.
Publicado: (2026)
VEGGIE: Instructional Editing and Reasoning Video Concepts with Grounded Generation
por: Yu, Shoubin, et al.
Publicado: (2025)
por: Yu, Shoubin, et al.
Publicado: (2025)
Extracting Training Data from Unconditional Diffusion Models
por: Chen, Yunhao, et al.
Publicado: (2024)
por: Chen, Yunhao, et al.
Publicado: (2024)
NAMER: Non-Autoregressive Modeling for Handwritten Mathematical Expression Recognition
por: Liu, Chenyu, et al.
Publicado: (2024)
por: Liu, Chenyu, et al.
Publicado: (2024)
Customize-A-Video: One-Shot Motion Customization of Text-to-Video Diffusion Models
por: Ren, Yixuan, et al.
Publicado: (2024)
por: Ren, Yixuan, et al.
Publicado: (2024)
Dense Policy: Bidirectional Autoregressive Learning of Actions
por: Su, Yue, et al.
Publicado: (2025)
por: Su, Yue, et al.
Publicado: (2025)
Learning Real-World Action-Video Dynamics with Heterogeneous Masked Autoregression
por: Wang, Lirui, et al.
Publicado: (2025)
por: Wang, Lirui, et al.
Publicado: (2025)
Corruption-Aware Training of Latent Video Diffusion Models for Robust Text-to-Video Generation
por: Maduabuchi, Chika, et al.
Publicado: (2025)
por: Maduabuchi, Chika, et al.
Publicado: (2025)
Vidar: Embodied Video Diffusion Model for Generalist Manipulation
por: Feng, Yao, et al.
Publicado: (2025)
por: Feng, Yao, et al.
Publicado: (2025)
Chain-of-Action: Trajectory Autoregressive Modeling for Robotic Manipulation
por: Zhang, Wenbo, et al.
Publicado: (2025)
por: Zhang, Wenbo, et al.
Publicado: (2025)
Progressive Compositionality in Text-to-Image Generative Models
por: Han, Evans Xu, et al.
Publicado: (2024)
por: Han, Evans Xu, et al.
Publicado: (2024)
Reward-Forcing: Autoregressive Video Generation with Reward Feedback
por: Zhang, Jingran, et al.
Publicado: (2026)
por: Zhang, Jingran, et al.
Publicado: (2026)
Frequency-Aware Autoregressive Modeling for Efficient High-Resolution Image Synthesis
por: Chen, Zhuokun, et al.
Publicado: (2025)
por: Chen, Zhuokun, et al.
Publicado: (2025)
Post-training Quantization for Text-to-Image Diffusion Models with Progressive Calibration and Activation Relaxing
por: Tang, Siao, et al.
Publicado: (2023)
por: Tang, Siao, et al.
Publicado: (2023)
Autoregressive Adversarial Post-Training for Real-Time Interactive Video Generation
por: Lin, Shanchuan, et al.
Publicado: (2025)
por: Lin, Shanchuan, et al.
Publicado: (2025)
Contextualized Diffusion Models for Text-Guided Image and Video Generation
por: Yang, Ling, et al.
Publicado: (2024)
por: Yang, Ling, et al.
Publicado: (2024)
Short-Form Videos and Mental Health: A Knowledge-Guided Neural Topic Model
por: Xie, Jiaheng, et al.
Publicado: (2024)
por: Xie, Jiaheng, et al.
Publicado: (2024)
Deconstructing Denoising Diffusion Models for Self-Supervised Learning
por: Chen, Xinlei, et al.
Publicado: (2024)
por: Chen, Xinlei, et al.
Publicado: (2024)
Zigzag Diffusion Sampling: Diffusion Models Can Self-Improve via Self-Reflection
por: Bai, Lichen, et al.
Publicado: (2024)
por: Bai, Lichen, et al.
Publicado: (2024)
Ejemplares similares
-
Carve3D: Improving Multi-view Reconstruction Consistency for Diffusion Models with RL Finetuning
por: Xie, Desai, et al.
Publicado: (2023) -
Rethinking Training Dynamics in Scale-wise Autoregressive Generation
por: Zhou, Gengze, et al.
Publicado: (2025) -
LRM-Zero: Training Large Reconstruction Models with Synthesized Data
por: Xie, Desai, et al.
Publicado: (2024) -
Pushing the Boundaries of State Space Models for Image and Video Generation
por: Hong, Yicong, et al.
Publicado: (2025) -
LRM: Large Reconstruction Model for Single Image to 3D
por: Hong, Yicong, et al.
Publicado: (2023)