activity
20152023
most citedFCNs in the Wild: Pixel-level Adversarial and Constraint-based Adaptation

692 citations · 1.7k across the 18 of their papers we have counts for

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Showing 2019Show all

5 papers · 1 filter

cs.CV2019★ 6 cited

Dynamic Scale Inference by Entropy Minimization

Dequan Wang, Evan Shelhamer, Bruno Olshausen +1

Given the variety of the visual world there is not one true scale for recognition: objects may appear at drastically different sizes across the visual field. Rather than enumerate…

cs.CV2019

Monocular Plan View Networks for Autonomous Driving

Dequan Wang, Coline Devin, Qi-Zhi Cai +2

Convolutions on monocular dash cam videos capture spatial invariances in the image plane but do not explicitly reason about distances and depth. We propose a simple transformation…

cs.CV2019★ 20 cited

Blurring the Line Between Structure and Learning to Optimize and Adapt Receptive Fields

Evan Shelhamer, Dequan Wang, Trevor Darrell

The visual world is vast and varied, but its variations divide into structured and unstructured factors. We compose free-form filters and structured Gaussian filters, optimized end…

cs.CV2019

Objects as Points

Xingyi Zhou, Dequan Wang, Philipp Krähenbühl

Detection identifies objects as axis-aligned boxes in an image. Most successful object detectors enumerate a nearly exhaustive list of potential object locations and classify each.…

cs.CV2019★ 8 cited

Convolutional Neural Networks on non-uniform geometrical signals using Euclidean spectral transformation

Chiyu "Max" Jiang, Dequan Wang, Jingwei Huang +2

Convolutional Neural Networks (CNN) have been successful in processing data signals that are uniformly sampled in the spatial domain (e.g., images). However, most data signals do n…