most citedIn Teacher We Trust: Learning Compressed Models for Pedestrian Detection

21 citations · 52 across the 5 of their papers we have counts for

collaborators

5 papers

cs.CV201913 cited

Learnable Embedding Space for Efficient Neural Architecture Compression

Shengcao Cao, Xiaofang Wang, Kris M. Kitani

We propose a method to incrementally learn an embedding space over the domain of network architectures, to enable the careful selection of architectures for evaluation during compr…

cs.CV20169 cited

Visual Compiler: Synthesizing a Scene-Specific Pedestrian Detector and Pose Estimator

Namhoon Lee, Xinshuo Weng, Vishnu Naresh Boddeti +4

We introduce the concept of a Visual Compiler that generates a scene specific pedestrian detector and pose estimator without any pedestrian observations. Given a single image and a…

cs.CV20161 cited

Deep Supervised Hashing with Triplet Labels

Xiaofang Wang, Yi Shi, Kris M. Kitani

Hashing is one of the most popular and powerful approximate nearest neighbor search techniques for large-scale image retrieval. Most traditional hashing methods first represent ima…

cs.CV20168 cited

Contextual Visual Similarity

Xiaofang Wang, Kris M. Kitani, Martial Hebert

Measuring visual similarity is critical for image understanding. But what makes two images similar? Most existing work on visual similarity assumes that images are similar because…

cs.CV201621 cited

In Teacher We Trust: Learning Compressed Models for Pedestrian Detection

Jonathan Shen, Noranart Vesdapunt, Vishnu N. Boddeti +1

Deep convolutional neural networks continue to advance the state-of-the-art in many domains as they grow bigger and more complex. It has been observed that many of the parameters o…