4 citations · 5 across the 7 of their papers we have counts for
7 papers · 1 filter
The Surprising Effectiveness of Video Diffusion Models for Hand Motion Reconstruction
Yuxi Wang, Chengkai Jin, Yufei Liu +6
4D hand motion reconstruction from egocentric video is bottlenecked by clear limitations of existing methods: image-based pipelines depend on a detector that fails under heavy occl…
Hand2World: Autoregressive Egocentric Interaction Generation via Free-Space Hand Gestures
Yuxi Wang, Wenqi Ouyang, Tianyi Wei +3
Egocentric interactive world models are essential for augmented reality and embodied AI, where visual generation must respond to user input with low latency, geometric consistency,…
WorldMem: Long-term Consistent World Simulation with Memory
Zeqi Xiao, Yushi Lan, Yifan Zhou +4
World simulation has gained increasing popularity due to its ability to model virtual environments and predict the consequences of actions. However, the limited temporal context wi…
Trajectory Attention for Fine-grained Video Motion Control
Zeqi Xiao, Wenqi Ouyang, Yifan Zhou +4
Recent advancements in video generation have been greatly driven by video diffusion models, with camera motion control emerging as a crucial challenge in creating view-customized v…
I2VEdit: First-Frame-Guided Video Editing via Image-to-Video Diffusion Models
Wenqi Ouyang, Yi Dong, Lei Yang +2
The remarkable generative capabilities of diffusion models have motivated extensive research in both image and video editing. Compared to video editing which faces additional chall…
RSFNet: A White-Box Image Retouching Approach using Region-Specific Color Filters
Wenqi Ouyang, Yi Dong, Xiaoyang Kang +3
Retouching images is an essential aspect of enhancing the visual appeal of photos. Although users often share common aesthetic preferences, their retouching methods may vary based…
DDColor: Towards Photo-Realistic Image Colorization via Dual Decoders
Xiaoyang Kang, Tao Yang, Wenqi Ouyang +3
Image colorization is a challenging problem due to multi-modal uncertainty and high ill-posedness. Directly training a deep neural network usually leads to incorrect semantic color…