Producing quality segmentation masks for images is a fundamental problem...
In this paper, we focus on the important yet understudied problem of
Con...
Recent studies on transfer learning have shown that selectively fine-tun...
Adapting large-scale pretrained models to various downstream tasks via
f...
Federated Learning (FL) seeks to distribute model training across local
...
Recent developments for Semi-Supervised Object Detection (SSOD) have sho...
Continual learning describes a setting where machine learning models lea...
Moving beyond testing on in-distribution data works on Out-of-Distributi...
It is well known that vision classification models suffer from poor
cali...
In this paper, we address bandwidth-limited and obstruction-prone
collab...
In this paper, we address the multi-robot collaborative perception probl...
Class imbalance is a fundamental problem in computer vision applications...
Neural Networks can perform poorly when the training label distribution ...
In image captioning where fluency is an important factor in evaluation, ...
While significant advances have been made for single-agent perception, m...
In this paper, we propose the problem of collaborative perception, where...
The fusion of multiple sensor modalities, especially through deep learni...