activity
20162022
most citedPartition-Aware Adaptive Switching Neural Networks for Post-Processing in HEVC

64 citations · 162 across the 10 of their papers we have counts for

collaborators
Showing cs.CVShow all

14 papers · 1 filter

cs.CV20221 cited

Controllable Augmentations for Video Representation Learning

Rui Qian, Weiyao Lin, John See +1

This paper focuses on self-supervised video representation learning. Most existing approaches follow the contrastive learning pipeline to construct positive and negative pairs by s…

cs.CV2021

Enhancing Self-supervised Video Representation Learning via Multi-level Feature Optimization

Rui Qian, Yuxi Li, Huabin Liu +5

The crux of self-supervised video representation learning is to build general features from unlabeled videos. However, most recent works have mainly focused on high-level semantics…

cs.CV20211 cited

Variational Pedestrian Detection

Yuang Zhang, Huanyu He, Jianguo Li +3

Pedestrian detection in a crowd is a challenging task due to a high number of mutually-occluding human instances, which brings ambiguity and optimization difficulties to the curren…

cs.CV2020

Delving into the Cyclic Mechanism in Semi-supervised Video Object Segmentation

Yuxi Li, Ning Xu, Jinlong Peng +2

In this paper, we address several inadequacies of current video object segmentation pipelines. Firstly, a cyclic mechanism is incorporated to the standard semi-supervised process t…

cs.CV2020

Finding Action Tubes with a Sparse-to-Dense Framework

Yuxi Li, Weiyao Lin, Tao Wang +5

The task of spatial-temporal action detection has attracted increasing attention among researchers. Existing dominant methods solve this problem by relying on short-term informatio…

cs.CV2020

CFAD: Coarse-to-Fine Action Detector for Spatiotemporal Action Localization

Yuxi Li, Weiyao Lin, John See +4

Most current pipelines for spatio-temporal action localization connect frame-wise or clip-wise detection results to generate action proposals, where only local information is explo…