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10/27/2022
Do Pre-trained Models Benefit Equally in Continual Learning?
Existing work on continual learning (CL) is primarily devoted to develop...
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06/10/2022
Is Self-Supervised Learning More Robust Than Supervised Learning?
Self-supervised contrastive learning is a powerful tool to learn visual ...
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12/08/2021
SIRfyN: Single Image Relighting from your Neighbors
We show how to relight a scene, depicted in a single image, such that (a...
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08/20/2021
Pixel Contrastive-Consistent Semi-Supervised Semantic Segmentation
We present a novel semi-supervised semantic segmentation method which jo...
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07/11/2021
Coordinate-wise Control Variates for Deep Policy Gradients
The control variates (CV) method is widely used in policy gradient estim...
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03/30/2021
DAP: Detection-Aware Pre-training with Weak Supervision
This paper presents a detection-aware pre-training (DAP) approach, which...
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09/13/2020
Efficient Competitive Self-Play Policy Optimization
Reinforcement learning from self-play has recently reported many success...
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07/15/2020
Boosting Weakly Supervised Object Detection with Progressive Knowledge Transfer
In this paper, we propose an effective knowledge transfer framework to b...
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02/21/2020
Disentangling Controllable Object through Video Prediction Improves Visual Reinforcement Learning
In many vision-based reinforcement learning (RL) problems, the agent con...
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05/31/2019
Sequence Modeling of Temporal Credit Assignment for Episodic Reinforcement Learning
Recent advances in deep reinforcement learning algorithms have shown gre...
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12/02/2018
Anchor Box Optimization for Object Detection
In this paper, we propose a general approach to optimize anchor boxes fo...
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03/08/2018
Rethinking Feature Distribution for Loss Functions in Image Classification
We propose a large-margin Gaussian Mixture (L-GM) loss for deep neural n...
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01/25/2017