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20142023
most citedFractalNet: Ultra-Deep Neural Networks without Residuals

622 citations · 1.4k across the 32 of their papers we have counts for

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Showing 2019Show all

5 papers · 1 filter

cs.CV2019★ 51 cited

DIODE: A Dense Indoor and Outdoor DEpth Dataset

Igor Vasiljevic, Nick Kolkin, Shanyi Zhang +8

We introduce DIODE, a dataset that contains thousands of diverse high resolution color images with accurate, dense, long-range depth measurements. DIODE (Dense Indoor/Outdoor DEpth…

cs.CV2019

Style Transfer by Relaxed Optimal Transport and Self-Similarity

Nicholas Kolkin, Jason Salavon, Greg Shakhnarovich

Style transfer algorithms strive to render the content of one image using the style of another. We propose Style Transfer by Relaxed Optimal Transport and Self-Similarity (STROTSS)…

cs.CV2019★ 34 cited

Deep Back-Projection Networks for Single Image Super-resolution

Muhammad Haris, Greg Shakhnarovich, Norimichi Ukita

Previous feed-forward architectures of recently proposed deep super-resolution networks learn the features of low-resolution inputs and the non-linear mapping from those to a high-…

cs.CV2019★ 11 cited

Recurrent Back-Projection Network for Video Super-Resolution

Muhammad Haris, Greg Shakhnarovich, Norimichi Ukita

We proposed a novel architecture for the problem of video super-resolution. We integrate spatial and temporal contexts from continuous video frames using a recurrent encoder-decode…

cs.LG2019★ 14 cited

Natural and Adversarial Error Detection using Invariance to Image Transformations

Yuval Bahat, Michal Irani, Gregory Shakhnarovich

We propose an approach to distinguish between correct and incorrect image classifications. Our approach can detect misclassifications which either occur ("na…