1 citations · 2 across the 11 of their papers we have counts for
11 papers
ACE-Ego-Hand: Repurposing Video Diffusion Models for Occlusion-Robust Egocentric 3D Hand Motion Recovery
Yufei Liu, Xixi Wang, Hao Li +8
Egocentric video offers scalable manipulation data for embodied AI, yet recovering metric 3D hand trajectories remains challenging due to severe object occlusion and frequent out-o…
HPSD: Hybrid-Policy Self-Distillation for Text-Image-to-Video Diffusion Models
Jiazi Bu, Pengyang Ling, Yujie Zhou +10
Text-Image-to-Video (TI2V) models are an emerging unified architecture, where a single model simultaneously supports text-to-video (T2V) and image-to-video (I2V) generation. Given…
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…
AdaGRPO: A Capability-Aware Adaptive Enhancement for Flow-based GRPO
Jiazi Bu, Pengyang Ling, Yujie Zhou +8
Group Relative Policy Optimization (GRPO) has demonstrated remarkable success in aligning text-to-image (T2I) flow models with human preferences. However, we have identified that t…
From Sparse to Dense: Multi-View GRPO for Flow Models via Augmented Condition Space
Jiazi Bu, Pengyang Ling, Yujie Zhou +8
Group Relative Policy Optimization (GRPO) has emerged as a powerful framework for preference alignment in text-to-image (T2I) flow models. However, we observe that the standard par…
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,…
PI-Light: Physics-Inspired Diffusion for Full-Image Relighting
Zhexin Liang, Zhaoxi Chen, Yongwei Chen +3
Full-image relighting remains a challenging problem due to the difficulty of collecting large-scale structured paired data, the difficulty of maintaining physical plausibility, and…
Neural LightRig: Unlocking Accurate Object Normal and Material Estimation with Multi-Light Diffusion
Zexin He, Tengfei Wang, Xin Huang +2
Recovering the geometry and materials of objects from a single image is challenging due to its under-constrained nature. In this paper, we present Neural LightRig, a novel framewor…
SAR3D: Autoregressive 3D Object Generation and Understanding via Multi-scale 3D VQVAE
Yongwei Chen, Yushi Lan, Shangchen Zhou +2
Autoregressive models have demonstrated remarkable success across various fields, from large language models (LLMs) to large multimodal models (LMMs) and 2D content generation, mov…
ComboVerse: Compositional 3D Assets Creation Using Spatially-Aware Diffusion Guidance
Yongwei Chen, Tengfei Wang, Tong Wu +3
Generating high-quality 3D assets from a given image is highly desirable in various applications such as AR/VR. Recent advances in single-image 3D generation explore feed-forward m…
WeatherDepth: Curriculum Contrastive Learning for Self-Supervised Depth Estimation under Adverse Weather Conditions
Jiyuan Wang, Chunyu Lin, Lang Nie +4
Depth estimation models have shown promising performance on clear scenes but fail to generalize to adverse weather conditions due to illumination variations, weather particles, etc…