351 citations · 1.1k across the 28 of their papers we have counts for
8 papers · 1 filter
Learned Variable-Rate Multi-Frequency Image Compression using Modulated Generalized Octave Convolution
Jianping Lin, Mohammad Akbari, Haisheng Fu +7
In this proposal, we design a learned multi-frequency image compression approach that uses generalized octave convolutions to factorize the latent representations into high-frequen…
Learning Trailer Moments in Full-Length Movies
Lezi Wang, Dong Liu, Rohit Puri +1
A movie's key moments stand out of the screenplay to grab an audience's attention and make movie browsing efficient. But a lack of annotations makes the existing approaches not app…
Efficient Integer-Arithmetic-Only Convolutional Neural Networks
Hengrui Zhao, Dong Liu, Houqiang Li
Integer-arithmetic-only networks have been demonstrated effective to reduce computational cost and to ensure cross-platform consistency. However, previous works usually report a de…
Foreground-Background Imbalance Problem in Deep Object Detectors: A Review
Joya Chen, Qi Wu, Dong Liu +1
Recent years have witnessed the remarkable developments made by deep learning techniques for object detection, a fundamentally challenging problem of computer vision. Nevertheless,…
Transferring and Regularizing Prediction for Semantic Segmentation
Yiheng Zhang, Zhaofan Qiu, Ting Yao +3
Semantic segmentation often requires a large set of images with pixel-level annotations. In the view of extremely expensive expert labeling, recent research has shown that the mode…
M-LVC: Multiple Frames Prediction for Learned Video Compression
Jianping Lin, Dong Liu, Houqiang Li +1
We propose an end-to-end learned video compression scheme for low-latency scenarios. Previous methods are limited in using the previous one frame as reference. Our method introduce…
Is There Tradeoff between Spatial and Temporal in Video Super-Resolution?
Haochen Zhang, Dong Liu, Zhiwei Xiong
Recent advances of deep learning lead to great success of image and video super-resolution (SR) methods that are based on convolutional neural networks (CNN). For video SR, advance…
Dual Temporal Memory Network for Efficient Video Object Segmentation
Kaihua Zhang, Long Wang, Dong Liu +3
Video Object Segmentation (VOS) is typically formulated in a semi-supervised setting. Given the ground-truth segmentation mask on the first frame, the task of VOS is to track and s…