"GenStereo: Towards Open-World Generation of Stereo Images and Unsupervised Matching" @ #ICCV2025
TL;DR: Is it possible to hallucinate a stereo pair for an image? Is that useful for training unsupervised stereo matching methods? Yes and YES!
qjizhi.github.io/genstereo/
30.09.2025 21:54 — 👍 2 🔁 0 💬 0 📌 0
Global and Local Entailment Learning for Natural World Imagery at #ICCV2025. See you in a few weeks!
TL;DR: If you're using BioCLIP for something, give this a try. We make the learned embeddings pay more attention to the taxonomic hierarchy, and it often works better.
vishu26.github.io/RCME/
30.09.2025 21:50 — 👍 1 🔁 0 💬 0 📌 0
CINA Distinguished Speaker Series with Abby Stylianou
TraffickCam: Identifying Where Victims of Human Trafficking and Child Sexual Abuse are Photographed Join us on Wednesday, January 29 for the upcoming virtual CINA Distinguished Speaker Series event…
I'm giving a virtual talk tomorrow at 12pm EST about the work that I've done with @pless.bsky.social @rsouvenir19.bsky.social and @jacobsn.bsky.social on building image search tools to support the National Center for Missing and Exploited Children. Feel free to tune in. cina.gmu.edu/event/cina-d...
29.01.2025 02:44 — 👍 13 🔁 4 💬 0 📌 2
Our CVPR Workshop EarthVision, bridging computer vision and Earth observation, was accepted at #CVPR2025 for its 8th edition! Submit your papers by March 3 and stay tuned for more info : grss-ieee.org/events/earth...
13.01.2025 16:24 — 👍 27 🔁 8 💬 0 📌 0
This was a fun collaboration with Anindya, Srikumar, @aleksispi.bsky.social, Chongjie, and Eugene. It brings together our recent work on using reinforcement learning for geospatial search tasks and a long history of work on geolocalization. I encourage you to stop by to chat with Anindya!
04.12.2024 19:35 — 👍 6 🔁 0 💬 0 📌 0
Assoc. Prof. in computer science at Univ. Bretagne Sud / IRISA
Research in time-series analysis with applications to Earth observations
👩💻📈🛰️🌍
Researcher at Inria Montpellier, France. I work on computer vision / machine learning models for biodiversity and environmental issues.
Computer Vision, Explainable Deep Learning, Point Clouds, 3D Perception
#ecoacoustics, #biodiversity monitoring, #NatureTech, #tech4wildlife, #conservation, #SciComm, lemur lady
Engineer your way. Engineer at Washington University in St. Louis. #WashUengineers
Anti-cynic. Towards a weirder future. Reinforcement Learning, Autonomous Vehicles, transportation systems, the works. Asst. Prof at NYU
https://emerge-lab.github.io
https://www.admonymous.co/eugenevinitsky
Assistant Professor, Auburn University. Computer Vision researcher, Neurosymbolic Vision.
Website: https://saakur.github.io/
Professor of Computer Vision and AI at TU Munich, Director of the Munich Center for Machine Learning mcml.ai and of ELLIS Munich ellismunich.ai
cvg.cit.tum.de
Tenure-track Assistant Professor @ University of Bologna
Depth estimation and related stuff
I am a Research Scientist at Google Zurich working on 3d vision (https://m-niemeyer.github.io/)
Head of Video & Image Sense Lab | University of Amsterdam | Scientific Director Amsterdam AI | https://www.ceessnoek.info/
Deputy Scientific Director in charge of AI @Inria,
Co-director PEPR IA,
Research director @Inria Grenoble: Computer Vision, Machine Learning,
@ellis.eu Fellow
computer vision + machine learning. Perception at Zoox. Prev: Cobot, PhD. Arxiv every day.
Professor in Computer Vision at the University of York, vision/graphics/ML research, Boro @mfc.co.uk fan and climber
📍York, UK
🔗 https://www-users.york.ac.uk/~waps101/
Assistant Prof. at Yale School of the Environment. Political economy of climate and environment, land use change, remote sensing, causal ML. https://sanford-lab.github.io/
Professor at Michigan | Voxel51 Co-Founder and Chief Scientist | Creator, Builder, Writer, Coder, Human
Associate Professor & Co-Founder - Dynamical Deep Learning
Co-founder of Climate AI Nordics | Senior ML researcher at RISE | AI for the environment | PhD in computer vision | Spare time collapsologist
Increasing shared understanding of our world through community-led initiatives that make data easier to access and use.
radiant.earth
