1 citations · 1 across the 16 of their papers we have counts for
11 papers · 2 filters
HEIR: Learning Human-Entity Interactions with Functional Roles
Di Wen, Wenhao Guo, Yuedong Tan +15
Understanding human-entity interactions requires recovering each person-action event's participants, roles, and shared identities. This structure can support embodied agents by cla…
Hand-Aware Transition Modeling for Bimanual Procedural Anomaly Detection
Di Wen, Jimmy Weissert, Luc Maria Scherrer +7
Procedural anomaly detection in bimanual assembly requires judging each hand action against the execution so far. A corrective action may look unusual in isolation, while a visuall…
PROVIA: Procedure State Tracking for Online Mistake Detection in Egocentric Videos
Di Wen, Kailun Yang, Jimmy Weissert +7
An assistant watching egocentric video should notice a mistake from past frames alone, before the next step begins, and keep working once the person recovers. A mistake changes the…
Quo Vadis, Visual In-Context Learning? A Unified Benchmark Across Domains and Tasks
Pradnya Halady, Jiale Wei, Zdravko Marinov +2
Visual in-context learning has been proposed as a pathway towards dynamic models that can generate predictions based on a provided context and thereby can adapt to new vision tasks…
IMPACT-Scribe: Interactive Temporal Action Segmentation with Boundary Scribbles and Query Planning
Qian Yin, Di Wen, Kunyu Peng +11
Dense temporal annotation of procedural activity videos is vital for action understanding and embodied intelligence but remains labor-intensive due to reactive tools. Each correcti…
IMPACT-HOI: Supervisory Control for Onset-Anchored Partial HOI Event Construction
Haoshen Zhang, Di Wen, Kunyu Peng +12
We present IMPACT-HOI, a mixed-initiative framework for annotating egocentric procedural video by constructing structured event graphs for Human-Object Interactions (HOI), motivate…
IMPACT-CYCLE: A Contract-Based Multi-Agent System for Claim-Level Supervisory Correction of Long-Video Semantic Memory
Weitong Kong, Di Wen, Kunyu Peng +10
Correcting errors in long-video understanding is disproportionately costly: existing multimodal pipelines produce opaque, end-to-end outputs that expose no intermediate state for i…
Rethinking Video Human-Object Interaction: Set Prediction over Time for Unified Detection and Anticipation
Yuanhao Luo, Di Wen, Kunyu Peng +5
Video-based human-object interaction (HOI) understanding requires both detecting ongoing interactions and anticipating their future evolution. However, existing methods usually tre…
More than the Sum: Panorama-Language Models for Adverse Omni-Scenes
Weijia Fan, Ruiping Liu, Jiale Wei +7
Existing vision-language models (VLMs) are tailored for pinhole imagery, stitching multiple narrow field-of-view inputs to piece together a complete omni-scene understanding. Yet,…
SGR3 Model: Scene Graph Retrieval-Reasoning Model in 3D
Zirui Wang, Ruiping Liu, Yufan Chen +7
3D scene graphs provide a structured representation of object entities and their relationships, enabling high-level interpretation and reasoning for robots while remaining intuitiv…
Can we Trust Unreliable Voxels? Exploring 3D Semantic Occupancy Prediction under Label Noise
Wenxin Li, Kunyu Peng, Di Wen +6
3D semantic occupancy prediction is a cornerstone of robotic perception, yet real-world voxel annotations are inherently corrupted by structural artifacts and dynamic trailing effe…