49 citations · 184 across the 40 of their papers we have counts for
11 papers · 1 filter
Dual Prototypical Contrastive Learning for Few-shot Semantic Segmentation
Hyeongjun Kwon, Somi Jeong, Sunok Kim +1
We address the problem of few-shot semantic segmentation (FSS), which aims to segment novel class objects in a target image with a few annotated samples. Though recent advances hav…
DIML/CVL RGB-D Dataset: 2M RGB-D Images of Natural Indoor and Outdoor Scenes
Jaehoon Cho, Dongbo Min, Youngjung Kim +1
This manual is intended to provide a detailed description of the DIML/CVL RGB-D dataset. This dataset is comprised of 2M color images and their corresponding depth maps from a grea…
Wide and Narrow: Video Prediction from Context and Motion
Jaehoon Cho, Jiyoung Lee, Changjae Oh +2
Video prediction, forecasting the future frames from a sequence of input frames, is a challenging task since the view changes are influenced by various factors, such as the global…
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…
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…
CausalCity: Complex Simulations with Agency for Causal Discovery and Reasoning
Daniel McDuff, Yale Song, Jiyoung Lee +7
The ability to perform causal and counterfactual reasoning are central properties of human intelligence. Decision-making systems that can perform these types of reasoning have the…
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…
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…
Memory-guided Unsupervised Image-to-image Translation
Somi Jeong, Youngjung Kim, Eungbean Lee +1
We present a novel unsupervised framework for instance-level image-to-image translation. Although recent advances have been made by incorporating additional object annotations, exi…
Looking into Your Speech: Learning Cross-modal Affinity for Audio-visual Speech Separation
Jiyoung Lee, Soo-Whan Chung, Sunok Kim +2
In this paper, we address the problem of separating individual speech signals from videos using audio-visual neural processing. Most conventional approaches utilize frame-wise matc…
On the confidence of stereo matching in a deep-learning era: a quantitative evaluation
Matteo Poggi, Seungryong Kim, Fabio Tosi +5
Stereo matching is one of the most popular techniques to estimate dense depth maps by finding the disparity between matching pixels on two, synchronized and rectified images. Along…