11 papers · 1 filter
GT-SVJ: Generative-Transformer-Based Self-Supervised Video Judge For Efficient Video Reward Modeling
Shivanshu Shekhar, Uttaran Bhattacharya, Raghavendra Addanki +3
Aligning video generative models with human preferences remains challenging: current approaches rely on Vision-Language Models (VLMs) for reward modeling, but these models struggle…
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…
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…
SimMotionEdit: Text-Based Human Motion Editing with Motion Similarity Prediction
Zhengyuan Li, Kai Cheng, Anindita Ghosh +3
Text-based 3D human motion editing is a critical yet challenging task in computer vision and graphics. While training-free approaches have been explored, the recent release of the…
Speech2UnifiedExpressions: Synchronous Synthesis of Co-Speech Affective Face and Body Expressions from Affordable Inputs
Uttaran Bhattacharya, Aniket Bera, Dinesh Manocha
We present a multimodal learning-based method to simultaneously synthesize co-speech facial expressions and upper-body gestures for digital characters using RGB video data captured…
HanDiffuser: Text-to-Image Generation With Realistic Hand Appearances
Supreeth Narasimhaswamy, Uttaran Bhattacharya, Xiang Chen +3
Text-to-image generative models can generate high-quality humans, but realism is lost when generating hands. Common artifacts include irregular hand poses, shapes, incorrect number…