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7 papers · 2 filters
Neural Pruning via Growing Regularization
Huan Wang, Can Qin, Yulun Zhang +1
Regularization has long been utilized to learn sparsity in deep neural network pruning. However, its role is mainly explored in the small penalty strength regime. In this work, we…
Event-VPR: End-to-End Weakly Supervised Network Architecture for Event-based Visual Place Recognition
Delei Kong, Zheng Fang, Haojia Li +3
Traditional visual place recognition (VPR) methods generally use frame-based cameras, which is easy to fail due to dramatic illumination changes or fast motions. In this paper, we…
Progressively Guided Alternate Refinement Network for RGB-D Salient Object Detection
Shuhan Chen, Yun Fu
In this paper, we aim to develop an efficient and compact deep network for RGB-D salient object detection, where the depth image provides complementary information to boost perform…
Key Frame Proposal Network for Efficient Pose Estimation in Videos
Yuexi Zhang, Yin Wang, Octavia Camps +1
Human pose estimation in video relies on local information by either estimating each frame independently or tracking poses across frames. In this paper, we propose a novel method c…
HyperSTAR: Task-Aware Hyperparameters for Deep Networks
Gaurav Mittal, Chang Liu, Nikolaos Karianakis +3
While deep neural networks excel in solving visual recognition tasks, they require significant effort to find hyperparameters that make them work optimally. Hyperparameter Optimiza…
Zooming Slow-Mo: Fast and Accurate One-Stage Space-Time Video Super-Resolution
Xiaoyu Xiang, Yapeng Tian, Yulun Zhang +3
In this paper, we explore the space-time video super-resolution task, which aims to generate a high-resolution (HR) slow-motion video from a low frame rate (LFR), low-resolution (L…