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Anubhav Gupta

5 papers hereh-index 6217 citations11 works total

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

author position
  • first author1
  • middle author4

Across the 5 of 5 papers where every author was matched, so the position is known.

fields
  • cs.CV4
  • cs.RO1
same name
  • Anubhav Gupta — 3 papers, h 11
  • Anubhav Gupta — 2 papers, h 1
  • Anubhav Gupta — 2 papers
  • Anubhav Gupta — 1 paper
  • Anubhav Gupta — 1 paper, h 3
  • Anubhav Gupta — 1 paper, h 4

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
20242026
most citedMeasuring Style Similarity in Diffusion Models

1 citations · 1 across the 5 of their papers we have counts for

collaborators
Showing cs.CVShow all

4 papers · 1 filter

cs.CV2026

VidParse: Online Parsing of Egocentric Procedures Like a Pro

Anubhav Gupta, Archit Kambhamettu, Vatsal Agarwal +2

Translating continuous, noisy egocentric video streams into discrete, temporally ordered action steps is fraught with visual challenges. Heavy ego-motion, transient occlusions, and…

cs.CV2024

LEIA: Latent View-invariant Embeddings for Implicit 3D Articulation

Archana Swaminathan, Anubhav Gupta, Kamal Gupta +3

Neural Radiance Fields (NeRFs) have revolutionized the reconstruction of static scenes and objects in 3D, offering unprecedented quality. However, extending NeRFs to model dynamic…

cs.CV2024

Latent-INR: A Flexible Framework for Implicit Representations of Videos with Discriminative Semantics

Shishira R Maiya, Anubhav Gupta, Matthew Gwilliam +2

Implicit Neural Networks (INRs) have emerged as powerful representations to encode all forms of data, including images, videos, audios, and scenes. With video, many INRs for video…

cs.CV2024★ 1 cited

Measuring Style Similarity in Diffusion Models

Gowthami Somepalli, Anubhav Gupta, Kamal Gupta +5

Generative models are now widely used by graphic designers and artists. Prior works have shown that these models remember and often replicate content from their training data durin…

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