Recent studies on transfer learning have shown that selectively fine-tun...
Semi-supervised learning aims to train a model using limited labels.
Sta...
In Vision-and-Language Navigation (VLN), researchers typically take an i...
Adapting large-scale pretrained models to various downstream tasks via
f...
Recent developments for Semi-Supervised Object Detection (SSOD) have sho...
With the recent development of Semi-Supervised Object Detection (SS-OD)
...
We tackle the problem of domain adaptation in object detection, where th...
Semi-supervised learning, i.e., training networks with both labeled and
...
Recent state-of-the-art semi-supervised learning (SSL) methods use a
com...
Convolutional Neural Networks (CNNs) show impressive performance in the
...
In this paper, we propose the problem of collaborative perception, where...
Recent advances in semi-supervised learning methods rely on estimating
c...
When generating a sentence description for an image, it frequently remai...
As deep learning continues to make progress for challenging perception t...
The Vision-and-Language Navigation (VLN) task entails an agent following...
We present AdaFrame, a framework that adaptively selects relevant frames...
We address the problem of video captioning by grounding language generat...
Human actions often involve complex interactions across several inter-re...
Recent two-stream deep Convolutional Neural Networks (ConvNets) have mad...