4.3k citations
Counting papers with at most 25 authors, so collaboration author lists do not stand in for the people here.
- Seoul National UniversityKR1.2k papers
- The University of TokyoJP1.2k papers
- Panjab UniversityIN1.2k papers
- Centre National de la Recherche ScientifiqueFR1.1k papers
- Sungkyunkwan UniversityKR1.1k papers
- Wayne State UniversityUS990 papers
- Korea UniversityKR986 papers
- National Taiwan UniversityTW970 papers
- Istituto Nazionale di Fisica Nucleare, Sezione di TorinoIT941 papers
- Kyungpook National UniversityKR930 papers
- University of Science and Technology of ChinaCN930 papers
- University of Tennessee at KnoxvilleUS920 papers
24 papers · 2 filters
Temporal Shuffling for Defending Deep Action Recognition Models against Adversarial Attacks
Jaehui Hwang, Huan Zhang, Jun-Ho Choi +2
Recently, video-based action recognition methods using convolutional neural networks (CNNs) achieve remarkable recognition performance. However, there is still lack of understandin…
Amicable Aid: Perturbing Images to Improve Classification Performance
Juyeop Kim, Jun-Ho Choi, Soobeom Jang +1
While adversarial perturbation of images to attack deep image classification models pose serious security concerns in practice, this paper suggests a novel paradigm where the conce…
UBoCo : Unsupervised Boundary Contrastive Learning for Generic Event Boundary Detection
Hyolim Kang, Jinwoo Kim, Taehyun Kim +1
Generic Event Boundary Detection (GEBD) is a newly suggested video understanding task that aims to find one level deeper semantic boundaries of events. Bridging the gap between nat…
A Data-Driven Approach for Linear and Nonlinear Damage Detection Using Variational Mode Decomposition and GARCH Model
Vahid Reza Gharehbaghi, Hashem Kalbkhani, Ehsan Noroozinejad Farsangi +2
In this article, an original data-driven approach is proposed to detect both linear and nonlinear damage in structures using output-only responses. The method deploys variational m…
hSDB-instrument: Instrument Localization Database for Laparoscopic and Robotic Surgeries
Jihun Yoon, Jiwon Lee, Sunghwan Heo +9
Automated surgical instrument localization is an important technology to understand the surgical process and in order to analyze them to provide meaningful guidance during surgery…
Self-balanced Learning For Domain Generalization
Jin Kim, Jiyoung Lee, Jungin Park +2
Domain generalization aims to learn a prediction model on multi-domain source data such that the model can generalize to a target domain with unknown statistics. Most existing appr…
Look Who's Talking: Active Speaker Detection in the Wild
You Jin Kim, Hee-Soo Heo, Soyeon Choe +5
In this work, we present a novel audio-visual dataset for active speaker detection in the wild. A speaker is considered active when his or her face is visible and the voice is audi…
Learning Action Completeness from Points for Weakly-supervised Temporal Action Localization
Pilhyeon Lee, Hyeran Byun
We tackle the problem of localizing temporal intervals of actions with only a single frame label for each action instance for training. Owing to label sparsity, existing work fails…
Learning Canonical 3D Object Representation for Fine-Grained Recognition
Sunghun Joung, Seungryong Kim, Minsu Kim +2
We propose a novel framework for fine-grained object recognition that learns to recover object variation in 3D space from a single image, trained on an image collection without usi…
Light Lies: Optical Adversarial Attack
Kyulim Kim, JeongSoo Kim, Seungri Song +3
A significant amount of work has been done on adversarial attacks that inject imperceptible noise to images to deteriorate the image classification performance of deep models. Howe…
MKConv: Multidimensional Feature Representation for Point Cloud Analysis
Sungmin Woo, Dogyoon Lee, Sangwon Hwang +2
Despite the remarkable success of deep learning, an optimal convolution operation on point clouds remains elusive owing to their irregular data structure. Existing methods mainly f…
Winning the CVPR'2021 Kinetics-GEBD Challenge: Contrastive Learning Approach
Hyolim Kang, Jinwoo Kim, Kyungmin Kim +2
Generic Event Boundary Detection (GEBD) is a newly introduced task that aims to detect "general" event boundaries that correspond to natural human perception. In this paper, we int…
CATs: Cost Aggregation Transformers for Visual Correspondence
Seokju Cho, Sunghwan Hong, Sangryul Jeon +3
We propose a novel cost aggregation network, called Cost Aggregation Transformers (CATs), to find dense correspondences between semantically similar images with additional challeng…
Polygonal Point Set Tracking
Gunhee Nam, Miran Heo, Seoung Wug Oh +2
In this paper, we propose a novel learning-based polygonal point set tracking method. Compared to existing video object segmentation~(VOS) methods that propagate pixel-wise object…
AutoReCon: Neural Architecture Search-based Reconstruction for Data-free Compression
Baozhou Zhu, Peter Hofstee, Johan Peltenburg +2
Data-free compression raises a new challenge because the original training dataset for a pre-trained model to be compressed is not available due to privacy or transmission issues.…
Railroad is not a Train: Saliency as Pseudo-pixel Supervision for Weakly Supervised Semantic Segmentation
Seungho Lee, Minhyun Lee, Jongwuk Lee +1
Existing studies in weakly-supervised semantic segmentation (WSSS) using image-level weak supervision have several limitations: sparse object coverage, inaccurate object boundaries…
Bridge to Answer: Structure-aware Graph Interaction Network for Video Question Answering
Jungin Park, Jiyoung Lee, Kwanghoon Sohn
This paper presents a novel method, termed Bridge to Answer, to infer correct answers for questions about a given video by leveraging adequate graph interactions of heterogeneous c…
Temporally smooth online action detection using cycle-consistent future anticipation
Young Hwi Kim, Seonghyeon Nam, Seon Joo Kim
Many video understanding tasks work in the offline setting by assuming that the input video is given from the start to the end. However, many real-world problems require the online…
Students are the Best Teacher: Exit-Ensemble Distillation with Multi-Exits
Hojung Lee, Jong-Seok Lee
This paper proposes a novel knowledge distillation-based learning method to improve the classification performance of convolutional neural networks (CNNs) without a pre-trained tea…
Multiple Heads are Better than One: Few-shot Font Generation with Multiple Localized Experts
Song Park, Sanghyuk Chun, Junbum Cha +2
A few-shot font generation (FFG) method has to satisfy two objectives: the generated images should preserve the underlying global structure of the target character and present the…
Collective Decision of One-vs-Rest Networks for Open Set Recognition
Jaeyeon Jang, Chang Ouk Kim
Unknown examples that are unseen during training often appear in real-world machine learning tasks, and an intelligent self-learning system should be able to distinguish between kn…
Continuous Face Aging Generative Adversarial Networks
Seogkyu Jeon, Pilhyeon Lee, Kibeom Hong +1
Face aging is the task aiming to translate the faces in input images to designated ages. To simplify the problem, previous methods have limited themselves only able to produce disc…
A fully automated method for 3D individual tooth identification and segmentation in dental CBCT
Tae Jun Jang, Kang Cheol Kim, Hyun Cheol Cho +1
Accurate and automatic segmentation of three-dimensional (3D) individual teeth from cone-beam computerized tomography (CBCT) images is a challenging problem because of the difficul…
ArrowGAN : Learning to Generate Videos by Learning Arrow of Time
Kibeom Hong, Youngjung Uh, Hyeran Byun
Training GANs on videos is even more sophisticated than on images because videos have a distinguished dimension: time. While recent methods designed a dedicated architecture consid…