most citedDeblurring by Realistic Blurring

12 citations · 41 across the 5 of their papers we have counts for

collaborators

9 papers

cs.CV202011 cited

Learning Modality Interaction for Temporal Sentence Localization and Event Captioning in Videos

Shaoxiang Chen, Wenhao Jiang, Wei Liu +1

Automatically generating sentences to describe events and temporally localizing sentences in a video are two important tasks that bridge language and videos. Recent techniques leve…

cs.CV20207 cited

Unsupervised Deep Representation Learning for Real-Time Tracking

Ning Wang, Wengang Zhou, Yibing Song +3

The advancement of visual tracking has continuously been brought by deep learning models. Typically, supervised learning is employed to train these models with expensive labeled da…

cs.CV202012 cited

Deblurring by Realistic Blurring

Kaihao Zhang, Wenhan Luo, Yiran Zhong +4

Existing deep learning methods for image deblurring typically train models using pairs of sharp images and their blurred counterparts. However, synthetically blurring images do not…

cs.CV20209 cited

Adversarial Perturbations Prevail in the Y-Channel of the YCbCr Color Space

Camilo Pestana, Naveed Akhtar, Wei Liu +2

Deep learning offers state of the art solutions for image recognition. However, deep models are vulnerable to adversarial perturbations in images that are subtle but significantly…

cs.CV20192 cited

Empirical Autopsy of Deep Video Captioning Frameworks

Nayyer Aafaq, Naveed Akhtar, Wei Liu +1

Contemporary deep learning based video captioning follows encoder-decoder framework. In encoder, visual features are extracted with 2D/3D Convolutional Neural Networks (CNNs) and a…

cs.CV2019

Vatex Video Captioning Challenge 2020: Multi-View Features and Hybrid Reward Strategies for Video Captioning

Xinxin Zhu, Longteng Guo, Peng Yao +3

This report describes our solution for the VATEX Captioning Challenge 2020, which requires generating descriptions for the videos in both English and Chinese languages. We identifi…