activity
20202026
most citedEnd-to-End Supermask Pruning: Learning to Prune Image Captioning Models

23 citations · 37 across the 4 of their papers we have counts for

collaborators

5 papers

cs.CV2026

Beyond Exact Match: Task-Aware GRPO for Cross-Domain PCBA Visual Question Answering

Jia Li, Li Dai, Peng Jia +4

In automated Printed Circuit Board Assembly (PCBA) inspection, standards-guided decisions require systems to jointly reason over fine-grained visual cues, component semantics, and…

eess.IV2022★ 1 cited

Extremely Low-light Image Enhancement with Scene Text Restoration

Pohao Hsu, Che-Tsung Lin, Chun Chet Ng +5

Deep learning-based methods have made impressive progress in enhancing extremely low-light images - the image quality of the reconstructed images has generally improved. However, w…

cs.CV2022

ACORT: A Compact Object Relation Transformer for Parameter Efficient Image Captioning

Jia Huei Tan, Ying Hua Tan, Chee Seng Chan +1

Recent research that applies Transformer-based architectures to image captioning has resulted in state-of-the-art image captioning performance, capitalising on the success of Trans…

cs.CV2021★ 23 cited

End-to-End Supermask Pruning: Learning to Prune Image Captioning Models

Jia Huei Tan, Chee Seng Chan, Joon Huang Chuah

With the advancement of deep models, research work on image captioning has led to a remarkable gain in raw performance over the last decade, along with increasing model complexity…

cs.CV2020★ 13 cited

On the General Value of Evidence, and Bilingual Scene-Text Visual Question Answering

Xinyu Wang, Yuliang Liu, Chunhua Shen +6

Visual Question Answering (VQA) methods have made incredible progress, but suffer from a failure to generalize. This is visible in the fact that they are vulnerable to learning coi…