Search Results for author: Janghoon Choi

Found 7 papers, 5 papers with code

Meta-Learning with Task-Adaptive Loss Function for Few-Shot Learning

1 code implementation ICCV 2021 Sungyong Baik, Janghoon Choi, Heewon Kim, Dohee Cho, Jaesik Min, Kyoung Mu Lee

The problem lies in that each application and task may require different auxiliary loss function, especially when tasks are diverse and distinct.

Few-Shot Learning

Searching for Controllable Image Restoration Networks

no code implementations ICCV 2021 Heewon Kim, Sungyong Baik, Myungsub Choi, Janghoon Choi, Kyoung Mu Lee

Diverse user preferences over images have recently led to a great amount of interest in controlling the imagery effects for image restoration tasks.

4k Image Restoration +1

Meta-Learning with Adaptive Hyperparameters

2 code implementations NeurIPS 2020 Sungyong Baik, Myungsub Choi, Janghoon Choi, Heewon Kim, Kyoung Mu Lee

Despite its popularity, several recent works question the effectiveness of MAML when test tasks are different from training tasks, thus suggesting various task-conditioned methodology to improve the initialization.

Few-Shot Learning

Visual Tracking by TridentAlign and Context Embedding

1 code implementation14 Jul 2020 Janghoon Choi, Junseok Kwon, Kyoung Mu Lee

However, extensive scale variations of the target object and distractor objects with similar categories have consistently posed challenges in visual tracking.

Region Proposal Visual Tracking

Scene-Adaptive Video Frame Interpolation via Meta-Learning

1 code implementation CVPR 2020 Myungsub Choi, Janghoon Choi, Sungyong Baik, Tae Hyun Kim, Kyoung Mu Lee

Finally, we show that our meta-learning framework can be easily employed to any video frame interpolation network and can consistently improve its performance on multiple benchmark datasets.

Meta-Learning Test-time Adaptation +1

Deep Meta Learning for Real-Time Target-Aware Visual Tracking

no code implementations ICCV 2019 Janghoon Choi, Junseok Kwon, Kyoung Mu Lee

In this paper, we propose a novel on-line visual tracking framework based on the Siamese matching network and meta-learner network, which run at real-time speeds.

Meta-Learning Real-Time Visual Tracking

Real-time visual tracking by deep reinforced decision making

1 code implementation21 Feb 2017 Janghoon Choi, Junseok Kwon, Kyoung Mu Lee

In this paper, we introduce a novel real-time visual tracking algorithm based on a template selection strategy constructed by deep reinforcement learning methods.

Real-Time Visual Tracking reinforcement-learning +1

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