Anomaly detection (AD), aiming to find samples that deviate from the tra...
Video frame interpolation has been actively studied with the development...
Vision transformers have recently shown strong global context modeling
c...
Small targets are often submerged in cluttered backgrounds of infrared
i...
Albeit with varying degrees of progress in the field of Semi-Supervised
...
Contrastive learning has shown great potential in video representation
l...
Video Anomaly Detection (VAD) is an important topic in computer vision.
...
Sketch-based 3D shape retrieval (SBSR) is an important yet challenging t...
In this paper, we present a novel end-to-end group collaborative learnin...
Weakly-supervised temporal action localization (WTAL) in untrimmed video...
Image-level weakly supervised semantic segmentation (WSSS) is a fundamen...
Person search aims to jointly localize and identify a query person from
...
Domain generalizable person re-identification aims to apply a trained mo...
Person search aims to simultaneously localize and identify a query perso...
Action detection plays an important role in high-level video understandi...
Person search has recently emerged as a challenging task that jointly
ad...
Recent advances in self-supervised learning with instance-level contrast...
Learning to re-identify or retrieve a group of people across non-overlap...
Person search aims to simultaneously localize and identify a query perso...
Accurately describing and detecting 2D and 3D keypoints is crucial to
es...
Previous studies dominantly target at self-supervised learning on real-v...
The goal of few-shot learning is to learn a classifier that can recogniz...
Data augmentation is a powerful technique to increase the diversity of d...
Image contour based vision measurement is widely applied in robot
manipu...
Normalization techniques are essential for accelerating the training and...
Deep generative models have been successfully applied to Zero-Shot Learn...
Conventional unsupervised hashing methods usually take advantage of
simi...
Conditioning analysis uncovers the landscape of optimization objective b...
Removing the rain streaks from single image is still a challenging task,...
Deep Convolutional Neural Networks (CNNs), such as Dense Convolutional
N...
The Deep Convolutional Neural Networks (CNNs) have obtained a great succ...
Recent binary representation learning models usually require sophisticat...
In this paper, we propose an analysis mechanism based structured Analysi...
We propose a novel structured discriminative block-diagonal dictionary
l...
How to economically cluster large-scale multi-view images is a long-stan...
Person re-identification (ReID) aims at matching persons across differen...