16 citations · 27 across the 6 of their papers we have counts for
5 papers · 1 filter
INQUIRE: A Natural World Text-to-Image Retrieval Benchmark
Edward Vendrow, Omiros Pantazis, Alexander Shepard +5
We introduce INQUIRE, a text-to-image retrieval benchmark designed to challenge multimodal vision-language models on expert-level queries. INQUIRE includes iNaturalist 2024 (iNat24…
Deep learning-based ecological analysis of camera trap images is impacted by training data quality and quantity
Peggy A. Bevan, Omiros Pantazis, Holly Pringle +10
Large image collections generated from camera traps offer valuable insights into species richness, occupancy, and activity patterns, significantly aiding biodiversity monitoring. H…
SVL-Adapter: Self-Supervised Adapter for Vision-Language Pretrained Models
Omiros Pantazis, Gabriel Brostow, Kate Jones +1
Vision-language models such as CLIP are pretrained on large volumes of internet sourced image and text pairs, and have been shown to sometimes exhibit impressive zero- and low-shot…
Matching Multiple Perspectives for Efficient Representation Learning
Omiros Pantazis, Mathew Salvaris
Representation learning approaches typically rely on images of objects captured from a single perspective that are transformed using affine transformations. Additionally, self-supe…
Focus on the Positives: Self-Supervised Learning for Biodiversity Monitoring
Omiros Pantazis, Gabriel Brostow, Kate Jones +1
We address the problem of learning self-supervised representations from unlabeled image collections. Unlike existing approaches that attempt to learn useful features by maximizing…