activity
20232026
most citedDreamVideo: Composing Your Dream Videos with Customized Subject and Motion

6 citations · 12 across the 22 of their papers we have counts for

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Showing 2025Show all

6 papers · 1 filter

cs.CV2025

Towards Reason-Informed Video Editing in Unified Models with Self-Reflective Learning

Xinyu Liu, Hangjie Yuan, Yujie Wei +9

Unified video models exhibit strong capabilities in understanding and generation, yet they struggle with reason-informed visual editing even when equipped with powerful internal vi…

cs.CV2025

Routing Matters in MoE: Scaling Diffusion Transformers with Explicit Routing Guidance

Yujie Wei, Shiwei Zhang, Hangjie Yuan +8

Mixture-of-Experts (MoE) has emerged as a powerful paradigm for scaling model capacity while preserving computational efficiency. Despite its notable success in large language mode…

cs.CV2025

TTS-VAR: A Test-Time Scaling Framework for Visual Auto-Regressive Generation

Zhekai Chen, Ruihang Chu, Yukang Chen +4

Scaling visual generation models is essential for real-world content creation, yet requires substantial training and computational expenses. Alternatively, test-time scaling has ga…

cs.CV2025

SynMotion: Semantic-Visual Adaptation for Motion Customized Video Generation

Shuai Tan, Biao Gong, Yujie Wei +8

Diffusion-based video motion customization facilitates the acquisition of human motion representations from a few video samples, while achieving arbitrary subjects transfer through…

cs.CV2025

Taming Consistency Distillation for Accelerated Human Image Animation

Xiang Wang, Shiwei Zhang, Hangjie Yuan +5

Recent advancements in human image animation have been propelled by video diffusion models, yet their reliance on numerous iterative denoising steps results in high inference costs…

cs.CV2025

DreamRelation: Relation-Centric Video Customization

Yujie Wei, Shiwei Zhang, Hangjie Yuan +8

Relational video customization refers to the creation of personalized videos that depict user-specified relations between two subjects, a crucial task for comprehending real-world…