activity
20232026
most citedAccessLens: Auto-detecting Inaccessibility of Everyday Objects

6 citations · 6 across the 4 of their papers we have counts for

collaborators

6 papers

cs.CV2026

Generating a Paracosm for Training-Free Zero-Shot Composed Image Retrieval

Tong Wang, Yunhan Zhao, Shu Kong

Composed Image Retrieval (CIR) is the task of retrieving a target image from a database using a multimodal query, which consists of a reference image and a modification text. The t…

cs.CV2025

Solving Instance Detection from an Open-World Perspective

Qianqian Shen, Yunhan Zhao, Nahyun Kwon +3

Instance detection (InsDet) aims to localize specific object instances within a novel scene imagery based on given visual references. Technically, it requires proposal detection to…

cs.CV20246 cited

AccessLens: Auto-detecting Inaccessibility of Everyday Objects

Nahyun Kwon, Qian Lu, Muhammad Hasham Qazi +4

In our increasingly diverse society, everyday physical interfaces often present barriers, impacting individuals across various contexts. This oversight, from small cabinet knobs to…

cs.CV2023

Instance Tracking in 3D Scenes from Egocentric Videos

Yunhan Zhao, Haoyu Ma, Shu Kong +1

Egocentric sensors such as AR/VR devices capture human-object interactions and offer the potential to provide task-assistance by recalling 3D locations of objects of interest in th…

cs.CV2023

A High-Resolution Dataset for Instance Detection with Multi-View Instance Capture

Qianqian Shen, Yunhan Zhao, Nahyun Kwon +3

Instance detection (InsDet) is a long-lasting problem in robotics and computer vision, aiming to detect object instances (predefined by some visual examples) in a cluttered scene.…

cs.CV2023

Prompting Scientific Names for Zero-Shot Species Recognition

Shubham Parashar, Zhiqiu Lin, Yanan Li +1

Trained on web-scale image-text pairs, Vision-Language Models (VLMs) such as CLIP can recognize images of common objects in a zero-shot fashion. However, it is underexplored how to…