39 citations · 87 across the 9 of their papers we have counts for
13 papers · 1 filter
MulT: An End-to-End Multitask Learning Transformer
Deblina Bhattacharjee, Tong Zhang, Sabine Süsstrunk +1
We propose an end-to-end Multitask Learning Transformer framework, named MulT, to simultaneously learn multiple high-level vision tasks, including depth estimation, semantic segmen…
Leverage Your Local and Global Representations: A New Self-Supervised Learning Strategy
Tong Zhang, Congpei Qiu, Wei Ke +2
Self-supervised learning (SSL) methods aim to learn view-invariant representations by maximizing the similarity between the features extracted from different crops of the same imag…
Fidelity Estimation Improves Noisy-Image Classification With Pretrained Networks
Xiaoyu Lin, Deblina Bhattacharjee, Majed El Helou +1
Image classification has significantly improved using deep learning. This is mainly due to convolutional neural networks (CNNs) that are capable of learning rich feature extractors…
VIDIT: Virtual Image Dataset for Illumination Transfer
Majed El Helou, Ruofan Zhou, Johan Barthas +1
Deep image relighting is gaining more interest lately, as it allows photo enhancement through illumination-specific retouching without human effort. Aside from aesthetic enhancemen…
Divergence-Based Adaptive Extreme Video Completion
Majed El Helou, Ruofan Zhou, Frank Schmutz +2
Extreme image or video completion, where, for instance, we only retain 1% of pixels in random locations, allows for very cheap sampling in terms of the required pre-processing. The…
Evaluating Salient Object Detection in Natural Images with Multiple Objects having Multi-level Saliency
Gökhan Yildirim, Debashis Sen, Mohan Kankanhalli +1
Salient object detection is evaluated using binary ground truth with the labels being salient object class and background. In this paper, we corroborate based on three subjective e…