6 papers · 1 filter
VidLaDA: Bidirectional Diffusion Large Language Models for Efficient Video Understanding
Zhihao He, Tieyuan Chen, Kangyu Wang +6
Current Video Large Language Models (Video LLMs) typically encode frames via a vision encoder and employ an autoregressive (AR) LLM for understanding and generation. However, this…
Repeating Words for Video-Language Retrieval with Coarse-to-Fine Objectives
Haoyu Zhao, Jiaxi Gu, Shicong Wang +4
The explosive growth of video streaming presents challenges in achieving high accuracy and low training costs for video-language retrieval. However, existing methods rely on large-…
A Glimpse to Compress: Dynamic Visual Token Pruning for Large Vision-Language Models
Quan-Sheng Zeng, Yunheng Li, Qilong Wang +4
Visual token compression is critical for Large Vision-Language Models (LVLMs) to efficiently process high-resolution inputs. Existing methods that typically adopt fixed compression…
Aligning Anime Video Generation with Human Feedback
Bingwen Zhu, Yudong Jiang, Baohan Xu +5
Anime video generation faces significant challenges due to the scarcity of anime data and unusual motion patterns, leading to issues such as motion distortion and flickering artifa…
DynamiCtrl: Rethinking the Basic Structure and the Role of Text for High-quality Human Image Animation
Haoyu Zhao, Zhongang Qi, Cong Wang +5
With diffusion transformer (DiT) excelling in video generation, its use in specific tasks has drawn increasing attention. However, adapting DiT for pose-guided human image animatio…
EDEN: Enhanced Diffusion for High-quality Large-motion Video Frame Interpolation
Zihao Zhang, Haoran Chen, Haoyu Zhao +4
Handling complex or nonlinear motion patterns has long posed challenges for video frame interpolation. Although recent advances in diffusion-based methods offer improvements over t…