Search Results for author: Subeesh Vasu

Found 8 papers, 1 papers with code

HybridSDF: Combining Deep Implicit Shapes and Geometric Primitives for 3D Shape Representation and Manipulation

no code implementations22 Sep 2021 Subeesh Vasu, Nicolas Talabot, Artem Lukoianov, Pierre Baqué, Jonathan Donier, Pascal Fua

Deep implicit surfaces excel at modeling generic shapes but do not always capture the regularities present in manufactured objects, which is something simple geometric primitives are particularly good at.

3D Shape Representation

TopoAL: An Adversarial Learning Approach for Topology-Aware Road Segmentation

no code implementations ECCV 2020 Subeesh Vasu, Mateusz Kozinski, Leonardo Citraro, Pascal Fua

Instead, we use a more sophisticated discriminator that returns a label pyramid describing what portions of the road network are correct at several different scales.

Road Segmentation

Planar Geometry and Image Recovery from Motion-Blur

no code implementations7 Apr 2019 Kuldeep Purohit, Subeesh Vasu, M. Purnachandra Rao, A. N. Rajagopalan

We first propose an approach for estimation of normal of a planar scene from a single motion blurred observation.

Deblurring

Analyzing Perception-Distortion Tradeoff using Enhanced Perceptual Super-resolution Network

1 code implementation1 Nov 2018 Subeesh Vasu, Nimisha Thekke Madam, Rajagopalan A. N

Our work attempts to analyze the trade-off between distortion and perceptual quality for the problem of single image SR. To this end, we use the well-known SR architecture-enhanced deep super-resolution (EDSR) network and show that it can be adapted to achieve better perceptual quality for a specific range of the distortion measure.

Generative Adversarial Network Image Super-Resolution +1

Occlusion-Aware Rolling Shutter Rectification of 3D Scenes

no code implementations CVPR 2018 Subeesh Vasu, Mahesh Mohan M. R., A. N. Rajagopalan

Due to the sequential mechanism, images acquired with a moving camera are subjected to rolling shutter effect which manifests as geometric distortions.

From Local to Global: Edge Profiles to Camera Motion in Blurred Images

no code implementations CVPR 2017 Subeesh Vasu, A. N. Rajagopalan

In this work, we investigate the relation between the edge profiles present in a motion blurred image and the underlying camera motion responsible for causing the motion blur.

Deblurring Motion Estimation

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