140 citations · 599 across the 19 of their papers we have counts for
7 papers · 1 filter
TruNet: Short Videos Generation from Long Videos via Story-Preserving Truncation
Fan Yang, Xiao Liu, Dongliang He +5
In this work, we introduce a new problem, named as {\em story-preserving long video truncation}, that requires an algorithm to automatically truncate a long-duration video into mul…
Image Inpainting with Learnable Bidirectional Attention Maps
Chaohao Xie, Shaohui Liu, Chao Li +5
Most convolutional network (CNN)-based inpainting methods adopt standard convolution to indistinguishably treat valid pixels and holes, making them limited in handling irregular ho…
Deep Concept-wise Temporal Convolutional Networks for Action Localization
Xin Li, Tianwei Lin, Xiao Liu +7
Existing action localization approaches adopt shallow temporal convolutional networks (\ie, TCN) on 1D feature map extracted from video frames. In this paper, we empirically find t…
BMN: Boundary-Matching Network for Temporal Action Proposal Generation
Tianwei Lin, Xiao Liu, Xin Li +2
Temporal action proposal generation is an challenging and promising task which aims to locate temporal regions in real-world videos where action or event may occur. Current bottom-…
Adapting Image Super-Resolution State-of-the-arts and Learning Multi-model Ensemble for Video Super-Resolution
Chao Li, Dongliang He, Xiao Liu +2
Recently, image super-resolution has been widely studied and achieved significant progress by leveraging the power of deep convolutional neural networks. However, there has been li…
STGAN: A Unified Selective Transfer Network for Arbitrary Image Attribute Editing
Ming Liu, Yukang Ding, Min Xia +4
Arbitrary attribute editing generally can be tackled by incorporating encoder-decoder and generative adversarial networks. However, the bottleneck layer in encoder-decoder usually…
Read, Watch, and Move: Reinforcement Learning for Temporally Grounding Natural Language Descriptions in Videos
Dongliang He, Xiang Zhao, Jizhou Huang +3
The task of video grounding, which temporally localizes a natural language description in a video, plays an important role in understanding videos. Existing studies have adopted st…