384 citations · 975 across the 10 of their papers we have counts for
16 papers
Learning by Asking Questions
Ishan Misra, Ross Girshick, Rob Fergus +3
We introduce an interactive learning framework for the development and testing of intelligent visual systems, called learning-by-asking (LBA). We explore LBA in context of the Visu…
Transitive Invariance for Self-supervised Visual Representation Learning
Xiaolong Wang, Kaiming He, Abhinav Gupta
Learning visual representations with self-supervised learning has become popular in computer vision. The idea is to design auxiliary tasks where labels are free to obtain. Most of…
What Actions are Needed for Understanding Human Actions in Videos?
Gunnar A. Sigurdsson, Olga Russakovsky, Abhinav Gupta
What is the right way to reason about human activities? What directions forward are most promising? In this work, we analyze the current state of human activity understanding in vi…
Revisiting Unreasonable Effectiveness of Data in Deep Learning Era
Chen Sun, Abhinav Shrivastava, Saurabh Singh +1
The success of deep learning in vision can be attributed to: (a) models with high capacity; (b) increased computational power; and (c) availability of large-scale labeled data. Sin…
Temporal Dynamic Graph LSTM for Action-driven Video Object Detection
Yuan Yuan, Xiaodan Liang, Xiaolong Wang +2
In this paper, we investigate a weakly-supervised object detection framework. Most existing frameworks focus on using static images to learn object detectors. However, these detect…
WebVision Challenge: Visual Learning and Understanding With Web Data
Wen Li, Limin Wang, Wei Li +5
We present the 2017 WebVision Challenge, a public image recognition challenge designed for deep learning based on web images without instance-level human annotation. Following the…