7.5k citations
Counting papers with at most 25 authors, so collaboration author lists do not stand in for the people here.
- NAVER Cloud (South Korea)KR46 papers
- Seoul National UniversityKR27 papers
- Korea Advanced Institute of Science and TechnologyKR24 papers
- Yonsei UniversityKR17 papers
- Sungkyunkwan UniversityKR12 papers
- Korea UniversityKR9 papers
- Line Corporation (Japan)JP5 papers
- Virginia TechUS5 papers
- Inha UniversityKR4 papers
- Kootenay Association for Science & TechnologyCA4 papers
- University of TorontoCA4 papers
- Hong Kong University of Science and TechnologyHK3 papers
11 papers · 2 filters
Simultaneous Recognition of Horizontal and Vertical Text in Natural Images
Chankyu Choi, Youngmin Yoon, Junsu Lee +1
Recent state-of-the-art scene text recognition methods have primarily focused on horizontal text in images. However, in several Asian countries, including China, large amounts of t…
C3: Concentrated-Comprehensive Convolution and its application to semantic segmentation
Hyojin Park, Youngjoon Yoo, Geonseok Seo +3
One of the practical choices for making a lightweight semantic segmentation model is to combine a depth-wise separable convolution with a dilated convolution. However, the simple c…
Perfect match: Improved cross-modal embeddings for audio-visual synchronisation
Soo-Whan Chung, Joon Son Chung, Hong-Goo Kang
This paper proposes a new strategy for learning powerful cross-modal embeddings for audio-to-video synchronization. Here, we set up the problem as one of cross-modal retrieval, whe…
Multimodal Dual Attention Memory for Video Story Question Answering
Kyung-Min Kim, Seong-Ho Choi, Jin-Hwa Kim +1
We propose a video story question-answering (QA) architecture, Multimodal Dual Attention Memory (MDAM). The key idea is to use a dual attention mechanism with late fusion. MDAM use…
Semi-convolutional Operators for Instance Segmentation
David Novotny, Samuel Albanie, Diane Larlus +1
Object detection and instance segmentation are dominated by region-based methods such as Mask RCNN. However, there is a growing interest in reducing these problems to pixel labelin…
From handcrafted to deep local features
Gabriela Csurka, Christopher R. Dance, Martin Humenberger
This paper presents an overview of the evolution of local features from handcrafted to deep-learning-based methods, followed by a discussion of several benchmarks and papers evalua…
Vehicle Image Generation Going Well with The Surroundings
Jeesoo Kim, Jangho Kim, Jaeyoung Yoo +2
Since the generative neural networks have made a breakthrough in the image generation problem, lots of researches on their applications have been studied such as image restoration,…
Bilinear Attention Networks
Jin-Hwa Kim, Jaehyun Jun, Byoung-Tak Zhang
Attention networks in multimodal learning provide an efficient way to utilize given visual information selectively. However, the computational cost to learn attention distributions…
MC-GAN: Multi-conditional Generative Adversarial Network for Image Synthesis
Hyojin Park, YoungJoon Yoo, Nojun Kwak
In this paper, we introduce a new method for generating an object image from text attributes on a desired location, when the base image is given. One step further to the existing s…
Coloring with Words: Guiding Image Colorization Through Text-based Palette Generation
Hyojin Bahng, Seungjoo Yoo, Wonwoong Cho +4
This paper proposes a novel approach to generate multiple color palettes that reflect the semantics of input text and then colorize a given grayscale image according to the generat…
LCR-Net++: Multi-person 2D and 3D Pose Detection in Natural Images
Gregory Rogez, Philippe Weinzaepfel, Cordelia Schmid
We propose an end-to-end architecture for joint 2D and 3D human pose estimation in natural images. Key to our approach is the generation and scoring of a number of pose proposals p…