activity
20212026
most citedJoint Learning On The Hierarchy Representation for Fine-Grained Human Action Recognition

11 citations · 16 across the 4 of their papers we have counts for

collaborators

5 papers

cs.AI2026

AiSearch: Interactive Multi-Modal Search with VLMs

Ali Koksal, Mei Chee Leong, Vicky Sintunata +2

Modern retrieval systems must both be automated and interactive, allowing users to search and refine results in real time. We present AiSearch, a flexible multimodal retrieval fram…

cs.AI2026

Towards Annotation-Free Validation of MLLMs: A Vision-Language Logical Consistency Metric

Ying Gu, Mei Chee Leong, Hui Li Tan +3

Dominant accuracy evaluation might reward unwarranted guessing of Large Language Models, and it might not be applicable to novel tasks for model validation without ground-truth (gt…

cs.AI2026

Explicit Logic Channel for Validation and Enhancement of MLLMs on Zero-Shot Tasks

Mei Chee Leong, Ying Gu, Hui Li Tan +2

Frontier Multimodal Large Language Models (MLLMs) exhibit remarkable capabilities in Visual-Language Comprehension (VLC) tasks. However, they are often deployed as zero-shot soluti…

cs.CV2022★ 5 cited

Combined CNN Transformer Encoder for Enhanced Fine-grained Human Action Recognition

Mei Chee Leong, Haosong Zhang, Hui Li Tan +2

Fine-grained action recognition is a challenging task in computer vision. As fine-grained datasets have small inter-class variations in spatial and temporal space, fine-grained act…

cs.CV2021★ 11 cited

Joint Learning On The Hierarchy Representation for Fine-Grained Human Action Recognition

Mei Chee Leong, Hui Li Tan, Haosong Zhang +3

Fine-grained human action recognition is a core research topic in computer vision. Inspired by the recently proposed hierarchy representation of fine-grained actions in FineGym and…