3 papers
cs.CV2019
Cycle-SUM: Cycle-consistent Adversarial LSTM Networks for Unsupervised Video Summarization
Li Yuan, Francis EH Tay, Ping Li +2
In this paper, we present a novel unsupervised video summarization model that requires no manual annotation. The proposed model termed Cycle-SUM adopts a new cycle-consistent adver…
cs.CV2018
Object Relation Detection Based on One-shot Learning
Li Zhou, Jian Zhao, Jianshu Li +2
Detecting the relations among objects, such as "cat on sofa" and "person ride horse", is a crucial task in image understanding, and beneficial to bridging the semantic gap between…
cs.CV2018
Understanding Humans in Crowded Scenes: Deep Nested Adversarial Learning and A New Benchmark for Multi-Human Parsing
Jian Zhao, Jianshu Li, Yu Cheng +4
Despite the noticeable progress in perceptual tasks like detection, instance segmentation and human parsing, computers still perform unsatisfactorily on visually understanding huma…