20 citations · 35 across the 4 of their papers we have counts for
8 papers
Generic Event Boundary Detection: A Benchmark for Event Segmentation
Mike Zheng Shou, Stan Weixian Lei, Weiyao Wang +2
This paper presents a novel task together with a new benchmark for detecting generic, taxonomy-free event boundaries that segment a whole video into chunks. Conventional work in te…
How2Sign: A Large-scale Multimodal Dataset for Continuous American Sign Language
Amanda Duarte, Shruti Palaskar, Lucas Ventura +5
One of the factors that have hindered progress in the areas of sign language recognition, translation, and production is the absence of large annotated datasets. Towards this end,…
Don't Judge an Object by Its Context: Learning to Overcome Contextual Bias
Krishna Kumar Singh, Dhruv Mahajan, Kristen Grauman +3
Existing models often leverage co-occurrences between objects and their context to improve recognition accuracy. However, strongly relying on context risks a model's generalizabili…
From Patches to Pictures (PaQ-2-PiQ): Mapping the Perceptual Space of Picture Quality
Zhenqiang Ying, Haoran Niu, Praful Gupta +3
Blind or no-reference (NR) perceptual picture quality prediction is a difficult, unsolved problem of great consequence to the social and streaming media industries that impacts bil…
ClusterFit: Improving Generalization of Visual Representations
Xueting Yan, Ishan Misra, Abhinav Gupta +2
Pre-training convolutional neural networks with weakly-supervised and self-supervised strategies is becoming increasingly popular for several computer vision tasks. However, due to…
Large-scale weakly-supervised pre-training for video action recognition
Deepti Ghadiyaram, Matt Feiszli, Du Tran +3
Current fully-supervised video datasets consist of only a few hundred thousand videos and fewer than a thousand domain-specific labels. This hinders the progress towards advanced v…