Never having seen an object and heard its sound simultaneously, can the ...
The robustness of object detection models is a major concern when applie...
Existing adversarial attacks against Object Detectors (ODs) suffer from ...
We propose an efficient algorithm for matching two correlated
Erdős–Rény...
Current semantic segmentation models have achieved great success under t...
Instance segmentation of point clouds is a crucial task in 3D field with...
Detecting arbitrarily oriented tiny objects poses intense challenges to
...
As few-shot object detectors are often trained with abundant base sample...
The tilted viewing nature of the off-nadir aerial images brings severe
c...
Motivated by the problem of matching vertices in two correlated
Erdős-Ré...
For two correlated graphs which are independently sub-sampled from a com...
Modern object detectors have achieved impressive progress under the clos...
The problem of detecting edge correlation between two Erdős-Rényi
random...
Zero-shot semantic segmentation (ZS3) aims to segment the novel categori...
This report summarizes the results of Learning to Understand Aerial Imag...
We study the problem of reconstructing a perfect matching M^* hidden in ...
Recently, object detection in aerial images has gained much attention in...
Unsupervised representation learning achieves promising performances in
...
In the past decade, object detection has achieved significant progress i...
Unsupervised contrastive learning achieves great success in learning ima...
The past decade has witnessed significant progress on detecting objects ...
Motivated by applications such as discovering strong ties in social netw...
Object detection in aerial images is an active yet challenging task in
c...
Random graph matching refers to recovering the underlying vertex
corresp...
We introduce the problem of hidden Hamiltonian cycle recovery, where the...
Object detection is an important and challenging problem in computer vis...