activity
20142026
most citedUnsupervised Learning of Visual Representations using Videos

195 citations · 1.4k across the 56 of their papers we have counts for

collaborators
Showing 2015Show all

10 papers · 1 filter

cs.CV2015★ 15 cited

Actions ~ Transformations

Xiaolong Wang, Ali Farhadi, Abhinav Gupta

What defines an action like "kicking ball"? We argue that the true meaning of an action lies in the change or transformation an action brings to the environment. In this paper, we…

cs.CV2015★ 10 cited

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…

cs.CV2015★ 195 cited

Unsupervised Learning of Visual Representations using Videos

Xiaolong Wang, Abhinav Gupta

Is strong supervision necessary for learning a good visual representation? Do we really need millions of semantically-labeled images to train a Convolutional Neural Network (CNN)?…

cs.CV2015★ 21 cited

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…

cs.CV2015★ 37 cited

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…

cs.CV2015★ 13 cited

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…