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20162026
most citedPN-Net: Conjoined Triple Deep Network for Learning Local Image Descriptors

154 citations · 605 across the 50 of their papers we have counts for

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Showing 2021 · cs.CVShow all

6 papers · 2 filters

cs.CV2021

NinjaDesc: Content-Concealing Visual Descriptors via Adversarial Learning

Tony Ng, Hyo Jin Kim, Vincent Lee +7

In the light of recent analyses on privacy-concerning scene revelation from visual descriptors, we develop descriptors that conceal the input image content. In particular, we propo…

cs.CV2021

ScaleNet: A Shallow Architecture for Scale Estimation

Axel Barroso-Laguna, Yurun Tian, Krystian Mikolajczyk

In this paper, we address the problem of estimating scale factors between images. We formulate the scale estimation problem as a prediction of a probability distribution over scale…

cs.CV2021★ 2 cited

Information Theoretic Representation Distillation

Roy Miles, Adrian Lopez Rodriguez, Krystian Mikolajczyk

Despite the empirical success of knowledge distillation, current state-of-the-art methods are computationally expensive to train, which makes them difficult to adopt in practice. T…

cs.CV2021★ 1 cited

Grasp-Oriented Fine-grained Cloth Segmentation without Real Supervision

Ruijie Ren, Mohit Gurnani Rajesh, Jordi Sanchez-Riera +6

Automatically detecting graspable regions from a single depth image is a key ingredient in cloth manipulation. The large variability of cloth deformations has motivated most of the…

cs.CV2021

Reconstructing Pruned Filters using Cheap Spatial Transformations

Roy Miles, Krystian Mikolajczyk

We present an efficient alternative to the convolutional layer using cheap spatial transformations. This construction exploits an inherent spatial redundancy of the learned convolu…

cs.CV2021★ 11 cited

Reassessing the Limitations of CNN Methods for Camera Pose Regression

Tony Ng, Adrian Lopez-Rodriguez, Vassileios Balntas +1

In this paper, we address the problem of camera pose estimation in outdoor and indoor scenarios. In comparison to the currently top-performing methods that rely on 2D to 3D matchin…