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Elisa Ricci

16 papers hereh-index 7355 citations17 works total

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

author position
  • middle author6
  • last author10

Across the 16 of 16 papers where every author was matched, so the position is known.

fields
  • cs.CV16
same name
  • Elisa Ricci — 24 papers, h 8
  • Elisa Ricci — 8 papers, h 3
  • Elisa Ricci — 6 papers, h 7
  • Elisa Ricci — 6 papers, h 1
  • Elisa Ricci — 5 papers, h 1
  • Elisa Ricci — 4 papers, h 2

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
20232026
most citedHarnessing Large Language Models for Training-free Video Anomaly Detection

2 citations · 3 across the 15 of their papers we have counts for

collaborators
Showing 2023Show all

4 papers · 1 filter

cs.CV2023

Diversified in-domain synthesis with efficient fine-tuning for few-shot classification

Victor G. Turrisi da Costa, Nicola Dall'Asen, Yiming Wang +2

Few-shot image classification aims to learn an image classifier using only a small set of labeled examples per class. A recent research direction for improving few-shot classifiers…

cs.CV2023

Collaborative Neural Painting

Nicola Dall'Asen, Willi Menapace, Elia Peruzzo +3

The process of painting fosters creativity and rational planning. However, existing generative AI mostly focuses on producing visually pleasant artworks, without emphasizing the pa…

cs.CV2023

Novel class discovery meets foundation models for 3D semantic segmentation

Luigi Riz, Cristiano Saltori, Yiming Wang +2

The task of Novel Class Discovery (NCD) in semantic segmentation entails training a model able to accurately segment unlabelled (novel) classes, relying on the available supervisio…

cs.CV2023★ 1 cited

Delving into CLIP latent space for Video Anomaly Recognition

Luca Zanella, Benedetta Liberatori, Willi Menapace +3

We tackle the complex problem of detecting and recognising anomalies in surveillance videos at the frame level, utilising only video-level supervision. We introduce the novel metho…

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