2 citations · 2 across the 6 of their papers we have counts for
5 papers · 1 filter
Pair-Free Coarse-to-Real Video Generation via Real-to-Coarse Image Supervision
Gonzalo Gómez-Nogales, Daohan Lu, Peiye Zhuang +2
Coarse-to-real (C2R) video generation converts coarse animation, simulation, or game-rendered videos into photorealistic videos while preserving scene layout, camera motion, and dy…
Coarse-to-Real: Generative Rendering for Populated Dynamic Scenes
Gonzalo Gomez-Nogales, Yicong Hong, Chongjian Ge +4
Traditional rendering pipelines rely on complex assets, accurate materials and lighting, and substantial computational resources to produce realistic imagery, yet they still face c…
Shape My Moves: Text-Driven Shape-Aware Synthesis of Human Motions
Ting-Hsuan Liao, Yi Zhou, Yu Shen +4
We explore how body shapes influence human motion synthesis, an aspect often overlooked in existing text-to-motion generation methods due to the ease of learning a homogenized, can…
HUMOTO: A 4D Dataset of Mocap Human Object Interactions
Jiaxin Lu, Chun-Hao Paul Huang, Uttaran Bhattacharya +2
We present Human Motions with Objects (HUMOTO), a high-fidelity dataset of human-object interactions for motion generation, computer vision, and robotics applications. Featuring 73…
Joint Diffusion for Universal Hand-Object Grasp Generation
Jinkun Cao, Jingyuan Liu, Kris Kitani +1
Predicting and generating human hand grasp over objects is critical for animation and robotic tasks. In this work, we focus on generating both the hand and objects in a grasp by a…