FGVC12 Workshop accepted to CVPR 2025, Nashville! CALL FOR PAPERS: https://t.co/60U5VTaYEl We discuss domains where expert knowledge is typically required and investigate artificial systems that can distinguish numerous very similar visual concepts. #CVPR #CVPR2025 #AI

The challenge is to classify volumetric µCT images of foraminifera tests. With only 210 labeled out of 18,426 volumes, the goal is to develop an efficient species classification method that minimizes annotation time, leveraging semi-supervised learning. [5/5]

With µCT scanning, we can scan thousands of forams in a single scan. By determining the species composition, we can efficiently understand how the environment has evolved. [4/5]

Since certain types of foraminifera only live in specific conditions, identifying the composition of the foraminifera sediments allows us to gain insights into past environmental conditions. [3/5]

Planktonic foraminifera (aka forams) are tiny organisms that inhabit the sea waters. Forams produce a unique calcium carbonate shell, called a test, which can consist of multiple chambers and elaborate structures. They are preserved in sea sediments for millions of years. [2/5]

Foram2025: Classifying microfossil volumes – the first step to understanding past climates. 👉 https://t.co/4U64XMHoFP @CVPR @kaggle #FGVC #CVPR #CVPR2025 @QIMCenter [1/5]

This competition aims to identify under-studied species based on their acoustic signatures from continuous audio data. The most effective solutions will demonstrate the ability to train reliable classifiers with limited labeled data. [4/4]

Conducting traditional surveys across large areas is costly. In contrast, passive acoustic monitoring, combined with modern ML techniques, enables conservationists to scale with greater temporal resolution, providing deeper insights into restoration interventions. [3/4]

Mobile and habitat-diverse species serve as valuable indicators of biodiversity change, as shifts in their assemblages and population dynamics can signal the success or failure of ecological restoration efforts. [2/4]

BirdCLEF25: Audio-based species identification focused on birds, amphibians, mammals, and insects in Colombia. 👉 https://t.co/jQrmPrbsKo @CVPR @LifeCLEF @kaggle #FGVC #CVPR #CVPR2025 [1/4]

For this competition the dataset contains 79 categories of marine animals of varying taxonomic ranks (e.g., family, genus, species). The challenge is to develop a model that can accurately classify these taxa and ideally leverage their taxonomic information to do so. [5/5]

In marine ecology, accurate taxonomic classification is essential for addressing fundamental questions: --> What species exist in a particular place? --> What is the ecosystem biodiversity and how does it change over time? [4/5]

Is that an Octopus rubescens, commonly found in this area, or is it an Octopus cyanea usually only observed in warm, tropical waters near Hawai’i? Accurate species classification is essential for understanding ocean ecosystems. [3/5]

Consider marine wildlife monitoring in coastal waters near California. Daily video footage analyzed by a standard ML model shows 2 octopuses, 1 shark, and 10 jellyfish - broad taxonomic categories. But species-level identification could reveal crucial details. [2/5]

FathomNet25: Navigating the Depths: Advancing Hierarchical Classification of Ocean Life https://t.co/rTT2iihh8r @FathomNet @CVPR @kaggle #FGVC #CVPR #CVPR2025 [1/5]

AnimalCLEF25: Multi-species individual animal identification 👉 https://t.co/0nm3Hpqzwl @CVPR @LifeCLEF @kaggle #FGVC #CVPR #CVPR2025 [1/4]

This challenge is about individual animal identification of sea turtles, salamanders, and Eurasian lynxes. Your goal will be to design a model that, for each image, determines whether the depicted animal is new (not in the training data) or known (to be classified). [4/4]

But there’s a catch: many current models overfit to the background instead of the animal’s unique features. That means they often fail in new environments. Hence, we need models that generalize better across diverse habitats and allow us to identify novel specimen. [3/4]

Identifying individual animals is key to understanding wildlife populations, movements, and behaviors. By automating this process using AI, researchers can gather powerful data to track migration, monitor ecosystems, and shape smarter conservation strategies. [2/4]

AnimalCLEF25: Multi-species individual animal identification 👉 https://t.co/0nm3Hpqzwl @CVPR @LifeCLEF @kaggle #FGVC #CVPR #CVPR2025 [1/4]

Predicting the plant species present at a location is helpful for biodiversity management & conservation scenarios. It allows for building high-res maps of species composition and related indicators such as species diversity, endangered species, and invasive species. [3/3]