24 citations · 46 across the 9 of their papers we have counts for
10 papers · 1 filter
Novel Single View Constraints for Manhattan 3D Line Reconstruction
Siddhant Ranade, Srikumar Ramalingam
This paper proposes a novel and exact method to reconstruct line-based 3D structure from a single image using Manhattan world assumption. This problem is a distinctly unsolved prob…
Empirical Bounds on Linear Regions of Deep Rectifier Networks
Thiago Serra, Srikumar Ramalingam
We can compare the expressiveness of neural networks that use rectified linear units (ReLUs) by the number of linear regions, which reflect the number of pieces of the piecewise li…
Simultaneous Edge Alignment and Learning
Zhiding Yu, Weiyang Liu, Yang Zou +4
Edge detection is among the most fundamental vision problems for its role in perceptual grouping and its wide applications. Recent advances in representation learning have led to c…
A Minimal Closed-Form Solution for Multi-Perspective Pose Estimation using Points and Lines
Pedro Miraldo, Tiago Dias, Srikumar Ramalingam
We propose a minimal solution for pose estimation using both points and lines for a multi-perspective camera. In this paper, we treat the multi-perspective camera as a collection o…
VLASE: Vehicle Localization by Aggregating Semantic Edges
Xin Yu, Sagar Chaturvedi, Chen Feng +4
In this paper, we propose VLASE, a framework to use semantic edge features from images to achieve on-road localization. Semantic edge features denote edge contours that separate pa…
How Could Polyhedral Theory Harness Deep Learning?
Thiago Serra, Christian Tjandraatmadja, Srikumar Ramalingam
The holy grail of deep learning is to come up with an automatic method to design optimal architectures for different applications. In other words, how can we effectively dimension…