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38 papers · 2 filters
Large-Scale Object Detection of Images from Network Cameras in Variable Ambient Lighting Conditions
Caleb Tung, Matthew R. Kelleher, Ryan J. Schlueter +5
Computer vision relies on labeled datasets for training and evaluation in detecting and recognizing objects. The popular computer vision program, YOLO ("You Only Look Once"), has b…
Exploring the Challenges towards Lifelong Fact Learning
Mohamed Elhoseiny, Francesca Babiloni, Rahaf Aljundi +3
So far life-long learning (LLL) has been studied in relatively small-scale and relatively artificial setups. Here, we introduce a new large-scale alternative. What makes the propos…
nocaps: novel object captioning at scale
Harsh Agrawal, Karan Desai, Yufei Wang +7
Image captioning models have achieved impressive results on datasets containing limited visual concepts and large amounts of paired image-caption training data. However, if these m…
Understanding and Improving Kernel Local Descriptors
Arun Mukundan, Giorgos Tolias, Andrei Bursuc +2
We propose a multiple-kernel local-patch descriptor based on efficient match kernels from pixel gradients. It combines two parametrizations of gradient position and direction, each…
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…
3D human pose estimation in video with temporal convolutions and semi-supervised training
Dario Pavllo, Christoph Feichtenhofer, David Grangier +1
In this work, we demonstrate that 3D poses in video can be effectively estimated with a fully convolutional model based on dilated temporal convolutions over 2D keypoints. We also…