60 citations · 93 across the 17 of their papers we have counts for
7 papers · 1 filter
Content-Diverse Comparisons improve IQA
William Thong, Jose Costa Pereira, Sarah Parisot +2
Image quality assessment (IQA) forms a natural and often straightforward undertaking for humans, yet effective automation of the task remains highly challenging. Recent metrics fro…
Label-Efficient Object Detection via Region Proposal Network Pre-Training
Nanqing Dong, Linus Ericsson, Yongxin Yang +2
Self-supervised pre-training, based on the pretext task of instance discrimination, has fueled the recent advance in label-efficient object detection. However, existing studies foc…
CLAD: A realistic Continual Learning benchmark for Autonomous Driving
Eli Verwimp, Kuo Yang, Sarah Parisot +5
In this paper we describe the design and the ideas motivating a new Continual Learning benchmark for Autonomous Driving (CLAD), that focuses on the problems of object classificatio…
Out-of-Distribution Detection with Class Ratio Estimation
Mingtian Zhang, Andi Zhang, Tim Z. Xiao +2
Density-based Out-of-distribution (OOD) detection has recently been shown unreliable for the task of detecting OOD images. Various density ratio based approaches achieve good empir…
Re-examining Distillation For Continual Object Detection
Eli Verwimp, Kuo Yang, Sarah Parisot +5
Training models continually to detect and classify objects, from new classes and new domains, remains an open problem. In this work, we conduct a thorough analysis of why and how o…
CroMo: Cross-Modal Learning for Monocular Depth Estimation
Yannick Verdié, Jifei Song, Barnabé Mas +3
Learning-based depth estimation has witnessed recent progress in multiple directions; from self-supervision using monocular video to supervised methods offering highest accuracy. C…