553 citations · 3.5k across the 54 of their papers we have counts for
11 papers · 1 filter
Shape from Shading through Shape Evolution
Dawei Yang, Jia Deng
In this paper, we address the shape-from-shading problem by training deep networks with synthetic images. Unlike conventional approaches that combine deep learning and synthetic im…
Premise Selection for Theorem Proving by Deep Graph Embedding
Mingzhe Wang, Yihe Tang, Jian Wang +1
We propose a deep learning-based approach to the problem of premise selection: selecting mathematical statements relevant for proving a given conjecture. We represent a higher-orde…
Scalable Annotation of Fine-Grained Categories Without Experts
Timnit Gebru, Jonathan Krause, Jia Deng +1
We present a crowdsourcing workflow to collect image annotations for visually similar synthetic categories without requiring experts. In animals, there is a direct link between tax…
Fine-Grained Car Detection for Visual Census Estimation
Timnit Gebru, Jonathan Krause, Yilun Wang +3
Targeted socioeconomic policies require an accurate understanding of a country's demographic makeup. To that end, the United States spends more than 1 billion dollars a year gather…
Pixels to Graphs by Associative Embedding
Alejandro Newell, Jia Deng
Graphs are a useful abstraction of image content. Not only can graphs represent details about individual objects in a scene but they can capture the interactions between pairs of o…
Temporal Action Localization by Structured Maximal Sums
Zehuan Yuan, Jonathan C. Stroud, Tong Lu +1
We address the problem of temporal action localization in videos. We pose action localization as a structured prediction over arbitrary-length temporal windows, where each window i…