336 citations · 854 across the 53 of their papers we have counts for
10 papers · 1 filter
Tracking by Associating Clips
Sanghyun Woo, Kwanyong Park, Seoung Wug Oh +2
The tracking-by-detection paradigm today has become the dominant method for multi-object tracking and works by detecting objects in each frame and then performing data association…
Bridging Images and Videos: A Simple Learning Framework for Large Vocabulary Video Object Detection
Sanghyun Woo, Kwanyong Park, Seoung Wug Oh +2
Scaling object taxonomies is one of the important steps toward a robust real-world deployment of recognition systems. We have faced remarkable progress in images since the introduc…
One-Shot Neural Fields for 3D Object Understanding
Valts Blukis, Taeyeop Lee, Jonathan Tremblay +5
We present a unified and compact scene representation for robotics, where each object in the scene is depicted by a latent code capturing geometry and appearance. This representati…
A Survey on Masked Autoencoder for Self-supervised Learning in Vision and Beyond
Chaoning Zhang, Chenshuang Zhang, Junha Song +3
Masked autoencoders are scalable vision learners, as the title of MAE \cite{he2022masked}, which suggests that self-supervised learning (SSL) in vision might undertake a similar tr…
Decoupled Adversarial Contrastive Learning for Self-supervised Adversarial Robustness
Chaoning Zhang, Kang Zhang, Chenshuang Zhang +4
Adversarial training (AT) for robust representation learning and self-supervised learning (SSL) for unsupervised representation learning are two active research fields. Integrating…
DRL-ISP: Multi-Objective Camera ISP with Deep Reinforcement Learning
Ukcheol Shin, Kyunghyun Lee, In So Kweon
In this paper, we propose a multi-objective camera ISP framework that utilizes Deep Reinforcement Learning (DRL) and camera ISP toolbox that consist of network-based and convention…
Labeling Where Adapting Fails: Cross-Domain Semantic Segmentation with Point Supervision via Active Selection
Fei Pan, Francois Rameau, Junsik Kim +1
Training models dedicated to semantic segmentation requires a large amount of pixel-wise annotated data. Due to their costly nature, these annotations might not be available for th…
Long-term Video Frame Interpolation via Feature Propagation
Dawit Mureja Argaw, In So Kweon
Video frame interpolation (VFI) works generally predict intermediate frame(s) by first estimating the motion between inputs and then warping the inputs to the target time with the…
Audio-Visual Fusion Layers for Event Type Aware Video Recognition
Arda Senocak, Junsik Kim, Tae-Hyun Oh +3
Human brain is continuously inundated with the multisensory information and their complex interactions coming from the outside world at any given moment. Such information is automa…
Maximizing Self-supervision from Thermal Image for Effective Self-supervised Learning of Depth and Ego-motion
Ukcheol Shin, Kyunghyun Lee, Byeong-Uk Lee +1
Recently, self-supervised learning of depth and ego-motion from thermal images shows strong robustness and reliability under challenging scenarios. However, the inherent thermal im…