Search Results for author: Kaleem Siddiqi

Found 13 papers, 4 papers with code

Average Outward Flux Skeletons for Environment Mapping and Topology Matching

no code implementations27 Nov 2021 Morteza Rezanejad, Babak Samari, Elham Karimi, Ioannis Rekleitis, Gregory Dudek, Kaleem Siddiqi

In topology matching between two given maps and their AOF skeletons, we first find correspondences between points on the AOF skeletons of two different environments.

Loop Closure Detection

Medial Spectral Coordinates for 3D Shape Analysis

no code implementations CVPR 2022 Morteza Rezanejad, Mohammad Khodadad, Hamidreza Mahyar, Herve Lombaert, Michael Gruninger, Dirk B. Walther, Kaleem Siddiqi

In recent years there has been a resurgence of interest in our community in the shape analysis of 3D objects represented by surface meshes, their voxelized interiors, or surface point clouds.

Autonomous Driving

EqR: Equivariant Representations for Data-Efficient Reinforcement Learning

no code implementations29 Sep 2021 Arnab Kumar Mondal, Vineet Jain, Kaleem Siddiqi, Siamak Ravanbakhsh

We study different notions of equivariance as an inductive bias in Reinforcement Learning (RL) and propose new mechanisms for recovering representations that are equivariant to both an agent’s action, and symmetry transformations of the state-action pairs.

Atari Games Inductive Bias +1

Mini-batch graphs for robust image classification

no code implementations22 Apr 2021 Arnab Kumar Mondal, Vineet Jain, Kaleem Siddiqi

Current deep learning models for classification tasks in computer vision are trained using mini-batches.

Classification General Classification +2

Group Equivariant Deep Reinforcement Learning

1 code implementation1 Jul 2020 Arnab Kumar Mondal, Pratheeksha Nair, Kaleem Siddiqi

In Reinforcement Learning (RL), Convolutional Neural Networks(CNNs) have been successfully applied as function approximators in Deep Q-Learning algorithms, which seek to learn action-value functions and policies in various environments.

Inductive Bias Q-Learning +1

Appearance Shock Grammar for Fast Medial Axis Extraction from Real Images

no code implementations CVPR 2020 Charles-Olivier Dufresne Camaro, Morteza Rezanejad, Stavros Tsogkas, Kaleem Siddiqi, Sven Dickinson

We make the following specific contributions: i) we extend the shock graph representation to the domain of real images, by generalizing the shock type definitions using local, appearance-based criteria; ii) we then use the rules of a Shock Grammar to guide our search for medial points, drastically reducing run time when compared to other methods, which exhaustively consider all points in the input image;iii) we remove the need for typical post-processing steps including thinning, non-maximum suppression, and grouping, by adhering to the Shock Grammar rules while deriving the medial axis solution; iv) finally, we raise some fundamental concerns with the evaluation scheme used in previous work and propose a more appropriate alternative for assessing the performance of medial axis extraction from scenes.

Affinity Graph Supervision for Visual Recognition

no code implementations CVPR 2020 Chu Wang, Babak Samari, Vladimir G. Kim, Siddhartha Chaudhuri, Kaleem Siddiqi

Affinity graphs are widely used in deep architectures, including graph convolutional neural networks and attention networks.

Image Classification

Dominant Set Clustering and Pooling for Multi-View 3D Object Recognition

1 code implementation4 Jun 2019 Chu Wang, Marcello Pelillo, Kaleem Siddiqi

We improve upon these methods by introducing a view clustering and pooling layer based on dominant sets.

3D Object Recognition

FAN: Focused Attention Networks

no code implementations27 May 2019 Chu Wang, Babak Samari, Vladimir Kim, Siddhartha Chaudhuri, Kaleem Siddiqi

Thus far the learning of attention weights has been driven solely by the minimization of task specific loss functions.

Document Classification Object Detection +1

DeepFlux for Skeletons in the Wild

2 code implementations CVPR 2019 Yukang Wang, Yongchao Xu, Stavros Tsogkas, Xiang Bai, Sven Dickinson, Kaleem Siddiqi

In the present article, we depart from this strategy by training a CNN to predict a two-dimensional vector field, which maps each scene point to a candidate skeleton pixel, in the spirit of flux-based skeletonization algorithms.

Edge Detection Object Skeleton Detection +2

White matter fiber analysis using kernel dictionary learning and sparsity priors

no code implementations15 Apr 2018 Kuldeep Kumar, Kaleem Siddiqi, Christian Desrosiers

Results highlight the ability of our method to group streamlines into plausible bundles and illustrate the impact of sparsity priors on the performance of the proposed methods.

Dictionary Learning

Local Spectral Graph Convolution for Point Set Feature Learning

1 code implementation ECCV 2018 Chu Wang, Babak Samari, Kaleem Siddiqi

In the present article, we propose to overcome this limitation by using spectral graph convolution on a local graph, combined with a novel graph pooling strategy.

3D Point Cloud Classification

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