output
20202022
most citedTransCAM: Transformer Attention-based CAM Refinement for Weakly Supervised Semantic Segmentation

95 citations

researchers with a paper here

Counting papers with at most 25 authors, so collaboration author lists do not stand in for the people here.

collaborating institutions

7 papers

cs.LG2022★ 21 cited

Significantly improving zero-shot X-ray pathology classification via fine-tuning pre-trained image-text encoders

Jongseong Jang, Daeun Kyung, Seung Hwan Kim +3

Deep neural networks are increasingly used in medical imaging for tasks such as pathological classification, but they face challenges due to the scarcity of high-quality, expert-la…

cs.AI2022★ 8 cited

Grouping-matrix based Graph Pooling with Adaptive Number of Clusters

Sung Moon Ko, Sungjun Cho, Dae-Woong Jeong +3

Graph pooling is a crucial operation for encoding hierarchical structures within graphs. Most existing graph pooling approaches formulate the problem as a node clustering task whic…

cs.CV2022★ 95 cited

TransCAM: Transformer Attention-based CAM Refinement for Weakly Supervised Semantic Segmentation

Ruiwen Li, Zheda Mai, Chiheb Trabelsi +3

Weakly supervised semantic segmentation (WSSS) with only image-level supervision is a challenging task. Most existing methods exploit Class Activation Maps (CAM) to generate pixel-…

cs.LG2021

Online Continual Learning in Image Classification: An Empirical Survey

Zheda Mai, Ruiwen Li, Jihwan Jeong +3

Online continual learning for image classification studies the problem of learning to classify images from an online stream of data and tasks, where tasks may include new classes (…

cs.LG2021★ 19 cited

Evolving Reinforcement Learning Algorithms

John D. Co-Reyes, Yingjie Miao, Daiyi Peng +5

We propose a method for meta-learning reinforcement learning algorithms by searching over the space of computational graphs which compute the loss function for a value-based model-…

cs.LG2020

Reinforcement Learning for Sparse-Reward Object-Interaction Tasks in a First-person Simulated 3D Environment

Wilka Carvalho, Anthony Liang, Kimin Lee +4

First-person object-interaction tasks in high-fidelity, 3D, simulated environments such as the AI2Thor virtual home-environment pose significant sample-efficiency challenges for re…

cs.LG2020★ 14 cited

Online Class-Incremental Continual Learning with Adversarial Shapley Value

Dongsub Shim, Zheda Mai, Jihwan Jeong +3

As image-based deep learning becomes pervasive on every device, from cell phones to smart watches, there is a growing need to develop methods that continually learn from data while…