activity
20192021
most citedLossless Image Compression through Super-Resolution

29 citations · 43 across the 3 of their papers we have counts for

collaborators

5 papers

cs.LG2021

Neighborhood-Aware Neural Architecture Search

Xiaofang Wang, Shengcao Cao, Mengtian Li +1

Existing neural architecture search (NAS) methods often return an architecture with good search performance but generalizes poorly to the test setting. To achieve better generaliza…

cs.LG20211 cited

Efficient Model Performance Estimation via Feature Histories

Shengcao Cao, Xiaofang Wang, Kris Kitani

An important step in the task of neural network design, such as hyper-parameter optimization (HPO) or neural architecture search (NAS), is the evaluation of a candidate model's per…

cs.CV2020

Rethinking Transformer-based Set Prediction for Object Detection

Zhiqing Sun, Shengcao Cao, Yiming Yang +1

DETR is a recently proposed Transformer-based method which views object detection as a set prediction problem and achieves state-of-the-art performance but demands extra-long train…

eess.IV202029 cited

Lossless Image Compression through Super-Resolution

Sheng Cao, Chao-Yuan Wu, Philipp Krähenbühl

We introduce a simple and efficient lossless image compression algorithm. We store a low resolution version of an image as raw pixels, followed by several iterations of lossless su…

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…