arXiv:2609.36937v1 Announce Type: cross
Abstract: Human image animation aims to transfer motion from a driving video to subjects in a reference image. Despite remarkable progress in video generation,...
By Sangeyl Lee, Seunghyun Shin, Seungho Park, Wooseok Jeon, Hae-Gon Jeon
Uni-HOI is a unified framework that learns the joint distribution among text, human motion, and object motion for 4D human‑object interaction (HOI). It uses large language models and two motion‑specific VQ‑VAEs to convert heterogeneous motion data into token sequences, enabling seamless integration of all three modalities. A two‑stage training strategy first captures correlations on a large‑scale HOI dataset and then fine‑tunes for specific tasks, achieving strong performance on text‑driven HOI generation, object‑motion‑driven human motion generation, and human‑motion‑driven object motion prediction.
By Mengfei Zhang, Jinlu Zhang, Zhigang Tu
SituHOI is a large‑scale RGB‑D dataset that captures full‑body human‑object interactions in 16 indoor rooms, comprising 18,429 annotated clips and about 86 hours of activity. The dataset pairs moving‑camera recordings with static scene scans, object geometry, language descriptions, and estimated human and object trajectories, all registered in a shared floor‑aligned frame via a pipeline that integrates camera localization, depth‑based alignment, human mesh recovery, and object tracking. The data enable the FlexHOI‑Bench benchmark for goal‑conditioned joint motion prediction, and a reference predictor, SharedHOI, demonstrates strong performance on world‑space accuracy and human‑object coordination.
whyItMatters":"The dataset provides scalable, scene‑aligned supervision for modeling human‑object interaction, addressing a key limitation of existing datasets and enabling more accurate motion prediction benchmarks."
By Qifan Wang, Qihang Fang, Boao Shi, Yushi Du, Pei Zhou, Siyan Dong, Yanchao Yang
arXiv:2610.10163v1 Announce Type: new
Abstract: Linking people's appearance and actions to character identities is essential for understanding video narratives. We present a framework for identity-aw...
By Anas Filali Razzouki, Killian Steunou, Khalil Guetari, Thomas Kling, Moun\^im El-Yacoubi, Yannis Tevissen
arXiv:2609.38615v1 Announce Type: cross
Abstract: Egocentric videos of human manipulation provide valuable visual experience for embodied intelligence, yet collecting such data at scale is costly. Ex...
By Hongjia Zhai, Xiyu Zhang, Haoran Zhang, Zhichao Ye, Haomin Liu, Guofeng Zhang, Ian Reid, Xingxing Zuo
arXiv:2510. 14904v4 Announce Type: replace-cross Abstract: Dense Video Object Captioning (DVOC) is the task of jointly detecting, tracking, and captioning object trajectories in a video, requiring the ability to understand spatio-temporal details and describe them in natural language.
By Gabriel Fiastre, Antoine Yang, Cordelia Schmid