1 code implementation • 26 Mar 2024 • Jae-hee So, Joonhwan Chang, Eunji Kim, Junho Na, JiYeon Choi, Jy-yong Sohn, Byung-Hoon Kim, Sang Hui Chu
Recent advancements in Large Language Models (LLMs) have accelerated their usage in various domains.
1 code implementation • 8 Jun 2023 • Seungryong Yoo, Eunji Kim, Dahuin Jung, Jungbeom Lee, Sungroh Yoon
Visual Prompt Tuning (VPT) is an effective tuning method for adapting pretrained Vision Transformers (ViTs) to downstream tasks.
Ranked #2 on Visual Prompt Tuning on VTAB-1k(Natural<7>)
2 code implementations • 2 Jun 2023 • Eunji Kim, Dahuin Jung, Sangha Park, Siwon Kim, Sungroh Yoon
To provide a reliable interpretation against this ambiguity, we propose Probabilistic Concept Bottleneck Models (ProbCBM).
no code implementations • 11 Apr 2022 • Jungbeom Lee, Eunji Kim, Jisoo Mok, Sungroh Yoon
This manipulation is realized in an anti-adversarial manner, so that the original image is perturbed along pixel gradients in directions opposite to those used in an adversarial attack.
no code implementations • CVPR 2022 • Eunji Kim, Siwon Kim, Jungbeom Lee, Hyunwoo Kim, Sungroh Yoon
Weakly supervised object localization aims to find a target object region in a given image with only weak supervision, such as image-level labels.
1 code implementation • CVPR 2022 • Jungbeom Lee, Seong Joon Oh, Sangdoo Yun, Junsuk Choe, Eunji Kim, Sungroh Yoon
However, training on class labels only, classifiers suffer from the spurious correlation between foreground and background cues (e. g. train and rail), fundamentally bounding the performance of WSSS.
Weakly supervised Semantic Segmentation Weakly-Supervised Semantic Segmentation
2 code implementations • 2 Dec 2021 • Sang-gil Lee, Eunji Kim, Jae Seok Bae, Jung Hoon Kim, Sungroh Yoon
The computer-aided diagnosis of focal liver lesions (FLLs) can help improve workflow and enable correct diagnoses; FLL detection is the first step in such a computer-aided diagnosis.
Automatic Liver And Tumor Segmentation Computed Tomography (CT) +4
no code implementations • 29 Sep 2021 • Jae Myung Kim, Eunji Kim, Sungroh Yoon, Jungwoo Lee, Cordelia Schmid, Zeynep Akata
Explaining a complex black-box system in a post-hoc manner is important to understand its predictions.
1 code implementation • CVPR 2021 • Eunji Kim, Siwon Kim, Minji Seo, Sungroh Yoon
Automated diagnosis using deep neural networks in chest radiography can help radiologists detect life-threatening diseases.
1 code implementation • CVPR 2021 • Jungbeom Lee, Eunji Kim, Sungroh Yoon
Weakly supervised semantic segmentation produces a pixel-level localization from a classifier, but it is likely to restrict its focus to a small discriminative region of the target object.
no code implementations • 1 Jan 2021 • Jae Myung Kim, Eunji Kim, Seokhyeon Ha, Sungroh Yoon, Jungwoo Lee
Saliency maps have been widely used to explain the behavior of an image classifier.
no code implementations • EMNLP 2020 • Siwon Kim, Jihun Yi, Eunji Kim, Sungroh Yoon
To demystify the "black box" property of deep neural networks for natural language processing (NLP), several methods have been proposed to interpret their predictions by measuring the change in prediction probability after erasing each token of an input.
1 code implementation • 23 Sep 2020 • Jihun Yi, Eunji Kim, Siwon Kim, Sungroh Yoon
IG map provides a class-independent answer to "How informative is each pixel?
no code implementations • ICCV 2019 • Jungbeom Lee, Eunji Kim, Sungmin Lee, Jangho Lee, Sungroh Yoon
We propose a method of using videos automatically harvested from the web to identify a larger region of the target object by using temporal information, which is not present in the static image.
no code implementations • CVPR 2019 • Jungbeom Lee, Eunji Kim, Sungmin Lee, Jangho Lee, Sungroh Yoon
The main obstacle to weakly supervised semantic image segmentation is the difficulty of obtaining pixel-level information from coarse image-level annotations.