6 citations · 14 across the 17 of their papers we have counts for
12 papers · 1 filter
RoMo: A Large-Scale, Richly Organized Dataset and Semantic Taxonomy for Human Motion Generation
Jiahao Zhang, Joseph Liu, Young-Yoon Lee +9
Success in generative modeling across language, image, and video demonstrates that large, well-curated datasets are the key driver for building capable models. 3D Human motion, how…
MemEye: A Visual-Centric Evaluation Framework for Multimodal Agent Memory
Minghao Guo, Qingyue Jiao, Zeru Shi +14
Long-term agent memory is increasingly multimodal, yet existing evaluations rarely test whether agents preserve the visual evidence needed for later reasoning. In prior work, many…
JACoP: Joint Alignment for Compliant Multi-Agent Prediction
Qingze Liu, Alen Mrdovic, Danrui Li +3
Stochastic Human Trajectory Prediction (HTP) using generative modeling has emerged as a significant area of research. Although state-of-the-art models excel in optimizing the accur…
ECTraj: Enhanced Consistency Training for Multi-Agent Trajectory Prediction
Alen Mrdovic, Qingze, Liu +6
Diffusion models for multi-agent trajectory prediction are limited by iterative denoising, which causes inference latency that hinders their use in time-critical settings like auto…
CASIM: Composite Aware Semantic Injection for Text to Motion Generation
Che-Jui Chang, Qingze Tony Liu, Honglu Zhou +2
Recent advances in generative modeling and tokenization have driven significant progress in text-to-motion generation, leading to enhanced quality and realism in generated motions.…
FCC: Fully Connected Correlation for One-Shot Segmentation
Seonghyeon Moon, Haein Kong, Muhammad Haris Khan +2
Few-shot segmentation (FSS) aims to segment the target object in a query image using only a small set of support images and masks. Therefore, having strong prior information for th…