1 citations · 2 across the 10 of their papers we have counts for
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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…
CAM3DNet: Comprehensively mining the multi-scale features for 3D Object Detection with Multi-View Cameras
Mingxi Pang, Dingheng Wang, Zekun Li +4
Query-based 3D object detection methods using multi-view images often struggle to efficiently leverage dynamic multi-scale information, e.g., the relationship between the object fe…
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…
UDAPose: Unsupervised Domain Adaptation for Low-Light Human Pose Estimation
Haopeng Chen, Yihao Ai, Kabeen Kim +3
Low-visibility scenarios, such as low-light conditions, pose significant challenges to human pose estimation due to the scarcity of annotated low-light datasets and the loss of vis…
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…
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…
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…
3DOT: Texture Transfer for 3DGS Objects from a Single Reference Image
Xiao Cao, Beibei Lin, Bo Wang +2
3D texture swapping allows for the customization of 3D object textures, enabling efficient and versatile visual transformations in 3D editing. While no dedicated method exists, ada…
EZ-HOI: VLM Adaptation via Guided Prompt Learning for Zero-Shot HOI Detection
Qinqian Lei, Bo Wang, Robby T. Tan
Detecting Human-Object Interactions (HOI) in zero-shot settings, where models must handle unseen classes, poses significant challenges. Existing methods that rely on aligning visua…
SSNeRF: Sparse View Semi-supervised Neural Radiance Fields with Augmentation
Xiao Cao, Beibei Lin, Bo Wang +2
Sparse view NeRF is challenging because limited input images lead to an under constrained optimization problem for volume rendering. Existing methods address this issue by relying…
Domain-Adaptive 2D Human Pose Estimation via Dual Teachers in Extremely Low-Light Conditions
Yihao Ai, Yifei Qi, Bo Wang +3
Existing 2D human pose estimation research predominantly concentrates on well-lit scenarios, with limited exploration of poor lighting conditions, which are a prevalent aspect of d…
Few-Shot Learning from Augmented Label-Uncertain Queries in Bongard-HOI
Qinqian Lei, Bo Wang, Robby T. Tan
Detecting human-object interactions (HOI) in a few-shot setting remains a challenge. Existing meta-learning methods struggle to extract representative features for classification d…