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S. Kumar

4 papers hereh-index 6121 citations7 works total

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

author position
  • first author1
  • middle author3

Across the 4 of 4 papers where every author was matched, so the position is known.

fields
  • cs.CV3
  • cs.NE1
same name
  • S. Kumar — 81 papers
  • S. Kumar — 66 papers
  • S. Kumar — 24 papers, h 28
  • S. Kumar — 18 papers, h 92
  • S. Kumar — 16 papers
  • S. Kumar — 15 papers, h 21

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

most cited3D-NVS: A 3D Supervision Approach for Next View Selection

2 citations · 2 across the 1 of their papers we have counts for

collaborators

4 papers

cs.CV2020★ 2 cited

3D-NVS: A 3D Supervision Approach for Next View Selection

Kumar Ashutosh, Saurabh Kumar, Subhasis Chaudhuri

We present a classification based approach for the next best view selection and show how we can plausibly obtain a supervisory signal for this task. The proposed approach is end-to…

cs.CV2020

Empowering Knowledge Distillation via Open Set Recognition for Robust 3D Point Cloud Classification

Ayush Bhardwaj, Sakshee Pimpale, Saurabh Kumar +1

Real-world scenarios pose several challenges to deep learning based computer vision techniques despite their tremendous success in research. Deeper models provide better performanc…

cs.NE2020

Distilling Spikes: Knowledge Distillation in Spiking Neural Networks

Ravi Kumar Kushawaha, Saurabh Kumar, Biplab Banerjee +1

Spiking Neural Networks (SNN) are energy-efficient computing architectures that exchange spikes for processing information, unlike classical Artificial Neural Networks (ANN). Due t…

cs.CV2019

Online Sensor Hallucination via Knowledge Distillation for Multimodal Image Classification

Saurabh Kumar, Biplab Banerjee, Subhasis Chaudhuri

We deal with the problem of information fusion driven satellite image/scene classification and propose a generic hallucination architecture considering that all the available senso…

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