5 papers
Token-Based Affordance Grounding with Large Vision-Language Models
Seung Il Lee, Qinqian Lei, Daguang Xu +4
Affordance grounding aims to localize image regions that support a specific action, serving as a core capability for physical intelligence and embodied perception. Previous studies…
A Study of Failure Modes in Two-Stage Human-Object Interaction Detection
Lemeng Wang, Qinqian Lei, Vidhi Bakshi +8
Human-object interaction (HOI) detection aims to detect interactions between humans and objects in images. While recent advances have improved performance on existing benchmarks, t…
SHOE: Semantic HOI Open-Vocabulary Evaluation Metric
Maja Noack, Qinqian Lei, Taipeng Tian +6
Open-vocabulary human-object interaction (HOI) detection is a step towards building scalable systems that generalize to unseen interactions in real-world scenarios and support grou…
CrossHOI-Bench: A Unified Benchmark for HOI Evaluation across Vision-Language Models and HOI-Specific Methods
Qinqian Lei, Bo Wang, Robby T. Tan
HOI detection has long been dominated by task-specific models, sometimes with early vision-language backbones such as CLIP. With the rise of large generative VLMs, a key question i…
HOLa: Zero-Shot HOI Detection with Low-Rank Decomposed VLM Feature Adaptation
Qinqian Lei, Bo Wang, Robby T. Tan
Zero-shot human-object interaction (HOI) detection remains a challenging task, particularly in generalizing to unseen actions. Existing methods address this challenge by tapping Vi…