18.1k citations · 35.5k across the 59 of their papers we have counts for
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Long-Term Feature Banks for Detailed Video Understanding
Chao-Yuan Wu, Christoph Feichtenhofer, Haoqi Fan +3
To understand the world, we humans constantly need to relate the present to the past, and put events in context. In this paper, we enable existing video models to do the same. We p…
Rethinking ImageNet Pre-training
Kaiming He, Ross Girshick, Piotr Dollár
We report competitive results on object detection and instance segmentation on the COCO dataset using standard models trained from random initialization. The results are no worse t…
Exploring the Limits of Weakly Supervised Pretraining
Dhruv Mahajan, Ross Girshick, Vignesh Ramanathan +5
State-of-the-art visual perception models for a wide range of tasks rely on supervised pretraining. ImageNet classification is the de facto pretraining task for these models. Yet,…
Low-Shot Learning from Imaginary Data
Yu-Xiong Wang, Ross Girshick, Martial Hebert +1
Humans can quickly learn new visual concepts, perhaps because they can easily visualize or imagine what novel objects look like from different views. Incorporating this ability to…
Panoptic Segmentation
Alexander Kirillov, Kaiming He, Ross Girshick +2
We propose and study a task we name panoptic segmentation (PS). Panoptic segmentation unifies the typically distinct tasks of semantic segmentation (assign a class label to each pi…