activity
20242026
most citedMSC: A Marine Wildlife Video Dataset with Grounded Segmentation and Clip-Level Captioning

1 citations · 2 across the 3 of their papers we have counts for

collaborators

5 papers

cs.CV2026

MarineEVT: Advancing Event-Centric Marine Video Understanding via Visual Tool Reasoning

Tuan-An To, Yuk-Kwan Wong, Tuan-Anh Vu +2

Recent Vision-Language Models (VLMs) have achieved remarkable success in visual understanding, driven by the growing availability of high-quality image-text pairs. However, the per…

cs.CV2025

ORCA: Object Recognition and Comprehension for Archiving Marine Species

Yuk-Kwan Wong, Haixin Liang, Zeyu Ma +6

Marine visual understanding is essential for monitoring and protecting marine ecosystems, enabling automatic and scalable biological surveys. However, progress is hindered by limit…

cs.CV20251 cited

MarineEval: Assessing the Marine Intelligence of Vision-Language Models

YuK-Kwan Wong, Tuan-An To, Jipeng Zhang +2

We have witnessed promising progress led by large language models (LLMs) and further vision language models (VLMs) in handling various queries as a general-purpose assistant. VLMs,…

cs.CV20251 cited

MSC: A Marine Wildlife Video Dataset with Grounded Segmentation and Clip-Level Captioning

Quang-Trung Truong, Yuk-Kwan Wong, Vo Hoang Kim Tuyen Dang +3

Marine videos present significant challenges for video understanding due to the dynamics of marine objects and the surrounding environment, camera motion, and the complexity of und…

cs.CV2024

CoralSCOP-LAT: Labeling and Analyzing Tool for Coral Reef Images with Dense Mask

Yuk-Kwan Wong, Ziqiang Zheng, Mingzhe Zhang +2

Coral reef imagery offers critical data for monitoring ecosystem health, in particular as the ease of image datasets continues to rapidly expand. Whilst semi-automated analytical p…