activity
20172021
most citedDiscriminative Latent Semantic Graph for Video Captioning

26 citations · 54 across the 4 of their papers we have counts for

collaborators
Showing cs.CVShow all

6 papers · 1 filter

cs.CV202126 cited

Discriminative Latent Semantic Graph for Video Captioning

Yang Bai, Junyan Wang, Yang Long +4

Video captioning aims to automatically generate natural language sentences that can describe the visual contents of a given video. Existing generative models like encoder-decoder f…

cs.CV202021 cited

Query Twice: Dual Mixture Attention Meta Learning for Video Summarization

Junyan Wang, Yang Bai, Yang Long +4

Video summarization aims to select representative frames to retain high-level information, which is usually solved by predicting the segment-wise importance score via a softmax fun…

cs.CV20197 cited

Order Matters: Shuffling Sequence Generation for Video Prediction

Junyan Wang, Bingzhang Hu, Yang Long +1

Predicting future frames in natural video sequences is a new challenge that is receiving increasing attention in the computer vision community. However, existing models suffer from…

cs.CV2018

Robust Cross-View Gait Recognition with Evidence: A Discriminant Gait GAN (DiGGAN) Approach

BingZhang Hu, Yu Guan, Yan Gao +3

Gait as a biometric trait has attracted much attention in many security and privacy applications such as identity recognition and authentication, during the last few decades. Becau…

cs.CV2018

Towards Universal Representation for Unseen Action Recognition

Yi Zhu, Yang Long, Yu Guan +2

Unseen Action Recognition (UAR) aims to recognise novel action categories without training examples. While previous methods focus on inner-dataset seen/unseen splits, this paper pr…

cs.CV2017

From Zero-shot Learning to Conventional Supervised Classification: Unseen Visual Data Synthesis

Yang Long, Li Liu, Ling Shao +3

Robust object recognition systems usually rely on powerful feature extraction mechanisms from a large number of real images. However, in many realistic applications, collecting suf…