93 citations · 242 across the 9 of their papers we have counts for
9 papers
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…
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…
In Defense of the Direct Perception of Affordances
David F. Fouhey, Xiaolong Wang, Abhinav Gupta
The field of functional recognition or affordance estimation from images has seen a revival in recent years. As originally proposed by Gibson, the affordances of a scene were direc…
Incorporating Structural Alternatives and Sharing into Hierarchy for Multiclass Object Recognition and Detection
Xiaolong Wang, Liang Lin, Lichao Huang +1
This paper proposes a reconfigurable model to recognize and detect multiclass (or multiview) objects with large variation in appearance. Compared with well acknowledged hierarchica…
Deep Joint Task Learning for Generic Object Extraction
Xiaolong Wang, Liliang Zhang, Liang Lin +2
This paper investigates how to extract objects-of-interest without relying on hand-craft features and sliding windows approaches, that aims to jointly solve two sub-tasks: (i) rapi…
Dynamical And-Or Graph Learning for Object Shape Modeling and Detection
Xiaolong Wang, Liang Lin
This paper studies a novel discriminative part-based model to represent and recognize object shapes with an "And-Or graph". We define this model consisting of three layers: the lea…