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20142023
most citedLearnable Gated Temporal Shift Module for Deep Video Inpainting

51 citations · 338 across the 55 of their papers we have counts for

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Showing 2019Show all

10 papers · 1 filter

cs.SD2019★ 23 cited

Deep Long Audio Inpainting

Ya-Liang Chang, Kuan-Ying Lee, Po-Yu Wu +2

Long (> 200 ms) audio inpainting, to recover a long missing part in an audio segment, could be widely applied to audio editing tasks and transmission loss recovery. It is a very ch…

eess.IV2019

Organ At Risk Segmentation with Multiple Modality

Kuan-Lun Tseng, Winston Hsu, Chun-ting Wu +2

With the development of image segmentation in computer vision, biomedical image segmentation have achieved remarkable progress on brain tumor segmentation and Organ At Risk (OAR) s…

cs.CV2019

A Unified Point-Based Framework for 3D Segmentation

Hung-Yueh Chiang, Yen-Liang Lin, Yueh-Cheng Liu +1

3D point cloud segmentation remains challenging for structureless and textureless regions. We present a new unified point-based framework for 3D point cloud segmentation that effec…

cs.CV2019★ 5 cited

Indoor Depth Completion with Boundary Consistency and Self-Attention

Yu-Kai Huang, Tsung-Han Wu, Yueh-Cheng Liu +1

Depth estimation features are helpful for 3D recognition. Commodity-grade depth cameras are able to capture depth and color image in real-time. However, glossy, transparent or dist…

cs.CV2019

Deep Multi-Kernel Convolutional LSTM Networks and an Attention-Based Mechanism for Videos

Sebastian Agethen, Winston H. Hsu

Action recognition greatly benefits motion understanding in video analysis. Recurrent networks such as long short-term memory (LSTM) networks are a popular choice for motion-aware…

cs.CV2019★ 51 cited

Learnable Gated Temporal Shift Module for Deep Video Inpainting

Ya-Liang Chang, Zhe Yu Liu, Kuan-Ying Lee +1

How to efficiently utilize temporal information to recover videos in a consistent way is the main issue for video inpainting problems. Conventional 2D CNNs have achieved good perfo…

cs.CV2019★ 2 cited

Video Question Generation via Cross-Modal Self-Attention Networks Learning

Yu-Siang Wang, Hung-Ting Su, Chen-Hsi Chang +2

We introduce a novel task, Video Question Generation (Video QG). A Video QG model automatically generates questions given a video clip and its corresponding dialogues. Video QG req…

cs.CV2019

FishNet: A Camera Localizer using Deep Recurrent Networks

Hsin-I Chen, Sebastian Agethen, Chiamin Wu +2

This paper proposes a robust localization system that employs deep learning for better scene representation, and enhances the accuracy of 6-DOF camera pose estimation. Inspired by…

cs.CV2019★ 6 cited

VORNet: Spatio-temporally Consistent Video Inpainting for Object Removal

Ya-Liang Chang, Zhe Yu Liu, Winston Hsu

Video object removal is a challenging task in video processing that often requires massive human efforts. Given the mask of the foreground object in each frame, the goal is to comp…

cs.CV2019★ 10 cited

Free-form Video Inpainting with 3D Gated Convolution and Temporal PatchGAN

Ya-Liang Chang, Zhe Yu Liu, Kuan-Ying Lee +1

Free-form video inpainting is a very challenging task that could be widely used for video editing such as text removal. Existing patch-based methods could not handle non-repetitive…