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20232026
most citedtinyCLAP: Distilling Constrastive Language-Audio Pretrained Models

5 citations · 8 across the 9 of their papers we have counts for

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5 papers · 1 filter

cs.CV2026

GaLe: memory-efficient Global Approximate and Local Exact features

Alberto Ancilotto, Elisabetta Farella

Embedded devices typically lack the resources of GPU-equipped machines, and existing inference methods suffer from either high computational overhead (patch-based) or accuracy loss…

cs.CV2025★ 2 cited

EHWGesture -- A dataset for multimodal understanding of clinical gestures

Gianluca Amprimo, Alberto Ancilotto, Alessandro Savino +5

Hand gesture understanding is essential for several applications in human-computer interaction, including automatic clinical assessment of hand dexterity. While deep learning has a…

cs.CV2024★ 1 cited

PaSTe: Improving the Efficiency of Visual Anomaly Detection at the Edge

Manuel Barusco, Francesco Borsatti, Davide Dalle Pezze +3

Visual Anomaly Detection (VAD) has gained significant research attention for its ability to identify anomalous images and pinpoint the specific areas responsible for the anomaly. A…

cs.CV2024

Latent Distillation for Continual Object Detection at the Edge

Francesco Pasti, Marina Ceccon, Davide Dalle Pezze +4

While numerous methods achieving remarkable performance exist in the Object Detection literature, addressing data distribution shifts remains challenging. Continual Learning (CL) o…

cs.CV2024

Replay Consolidation with Label Propagation for Continual Object Detection

Riccardo De Monte, Davide Dalle Pezze, Marina Ceccon +5

Continual Learning (CL) aims to learn new data while remembering previously acquired knowledge. In contrast to CL for image classification, CL for Object Detection faces additional…