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Amit Kumar

12 papers hereh-index 131k citations37 works total

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • first author6
  • middle author6

Across the 12 of 12 papers where every author was matched, so the position is known.

fields
  • cs.CV12
same name
  • Amit Kumar — 33 papers, h 41
  • Amit Kumar — 22 papers, h 11
  • Amit Kumar — 13 papers, h 0
  • Amit Kumar — 11 papers, h 9
  • Amit Kumar — 10 papers, h 4
  • Amit Kumar — 9 papers, h 8

Either other researchers who publish under this name, or the same person where the external sources have not merged their records.

identity via Semantic Scholar / OpenAlex

activity
20162022
most citedFace Alignment by Local Deep Descriptor Regression

20 citations · 32 across the 8 of their papers we have counts for

collaborators
Showing 2016Show all

4 papers · 1 filter

cs.CV2016

Unconstrained Still/Video-Based Face Verification with Deep Convolutional Neural Networks

Jun-Cheng Chen, Rajeev Ranjan, Swami Sankaranarayanan +5

Over the last five years, methods based on Deep Convolutional Neural Networks (DCNNs) have shown impressive performance improvements for object detection and recognition problems.…

cs.CV2016

Head Pose Estimation of Occluded Faces using Regularized Regression

Amit Kumar, Rishabh Bindal, Soumya Indela +1

This paper presents regression methods for estimation of head pose from occluded 2-D face images. The process primarily involves reconstructing a face from its occluded image, foll…

cs.CV2016★ 20 cited

Face Alignment by Local Deep Descriptor Regression

Amit Kumar, Rajeev Ranjan, Vishal Patel +1

We present an algorithm for extracting key-point descriptors using deep convolutional neural networks (CNN). Unlike many existing deep CNNs, our model computes local features aroun…

cs.CV2016

Towards the Design of an End-to-End Automated System for Image and Video-based Recognition

Rama Chellappa, Jun-Cheng Chen, Rajeev Ranjan +4

Over many decades, researchers working in object recognition have longed for an end-to-end automated system that will simply accept 2D or 3D image or videos as inputs and output th…

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Not affiliated with arXiv. Researcher data from Semantic Scholar (ODC-BY) and OpenAlex.