103 citations · 135 across the 6 of their papers we have counts for
6 papers
TAG: Boosting Text-VQA via Text-aware Visual Question-answer Generation
Jun Wang, Mingfei Gao, Yuqian Hu +5
Text-VQA aims at answering questions that require understanding the textual cues in an image. Despite the great progress of existing Text-VQA methods, their performance suffers fro…
Use All The Labels: A Hierarchical Multi-Label Contrastive Learning Framework
Shu Zhang, Ran Xu, Caiming Xiong +1
Current contrastive learning frameworks focus on leveraging a single supervisory signal to learn representations, which limits the efficacy on unseen data and downstream tasks. In…
Burn After Reading: Online Adaptation for Cross-domain Streaming Data
Luyu Yang, Mingfei Gao, Zeyuan Chen +3
In the context of online privacy, many methods propose complex privacy and security preserving measures to protect sensitive data. In this paper, we argue that: not storing any sen…
Value Retrieval with Arbitrary Queries for Form-like Documents
Mingfei Gao, Le Xue, Chetan Ramaiah +3
We propose value retrieval with arbitrary queries for form-like documents to reduce human effort of processing forms. Unlike previous methods that only address a fixed set of field…
Proposal Learning for Semi-Supervised Object Detection
Peng Tang, Chetan Ramaiah, Yan Wang +2
In this paper, we focus on semi-supervised object detection to boost performance of proposal-based object detectors (a.k.a. two-stage object detectors) by training on both labeled…
Challenges in Representation Learning: A report on three machine learning contests
Ian J. Goodfellow, Dumitru Erhan, Pierre Luc Carrier +25
The ICML 2013 Workshop on Challenges in Representation Learning focused on three challenges: the black box learning challenge, the facial expression recognition challenge, and the…