Our Embodied AI (https://embodied-ai.tech/) is also an art piece at #CVPR2026 art gallery!
Watch the backend representation of an AI system that moves a dancer's body with muscle stimulation.
Video: https://youtu.be/iRg6_SKpKrI
(See all art pieces at #CVPR: https://thecvf-art.com/archive.php?year=2026)
RE: https://sigmoid.social/@jaom7/116640689544313929
I will be at #CVPR2026 these days presenting our #TriLite method for weakly-supervised object localization. Get in touch in case you would like to discuss about #WSOL or #AI #Interpretability in general.
Long-term behavioral monitoring of individual animals is crucial for studying behavioral changes that occur over different time scales, especially for conservation and evolutionary biology. Computer vision methods have proven to benefit biodiversity monitoring, but automated behavior monitoring in wild populations remains challenging. This stems from the lack of datasets that cover a range of computer vision tasks necessary to extract biologically meaningful measurements of individual animals. Here, we introduce such a dataset (CHIRP) with a new method (CORVID) for individual re-identification of wild birds. The CHIRP (Combining beHaviour, Individual Re-identification and Postures) dataset is curated from a long-term population of wild Siberian jays studied in Swedish Lapland, supporting re-identification (re-id), action recognition, 2D keypoint estimation, object detection, and instance segmentation. In addition to traditional task-specific benchmarking, we introduce application-specific benchmarking with biologically relevant metrics (feeding rates, co-occurrence rates) to evaluate the performance of models in real-world use cases. Finally, we present CORVID (COlouR-based Video re-ID), a novel pipeline for individual identification of birds based on the segmentation and classification of colored leg rings, a widespread approach for visual identification of individual birds. CORVID offers a probability-based id tracking method by matching the detected combination of color rings with a database. We use application-specific benchmarking to show that CORVID outperforms state-of-the-art re-id methods. We hope this work offers the community a blueprint for curating real-world datasets from ethically approved biological studies to bridge the gap between computer vision research and biological applications.
I'm thinking back to 2021 when I was writing my thesis in university and had to read academic research papers every day.
The authors (all Israeli) of the deep learning papers I had to read in 2021, shared this in June 2024.
This repository contains the official implementation of "FastVLM: Efficient Vision Encoding for Vision Language Models" - CVPR 2025 - apple/ml-fastvlm
The OpenCV Perception Challenge for Bin-Picking is in full-swing, with teams submitting solutions to the leaderboard. If you're in the robotics or AI space, this is a great way to test your skills, win a share of the $60,000 in prizes, and most excitingly be part of an official CVPR Workshop at CVPR 2025 in Nashville!
Sign up to participate: https://bpc.opencv.org/web/challenges/challenge-page/1/overview
See the leaderboard: https://bpc.opencv.org/web/challenges/challenge-page/1/leaderboard/1
#OpenCV #ComputerVision #AI #BPC2025 #Robotics #Competition #CVPR
A competition focused on the real-world robustness of 6DoF solutions for the industry. This will involve estimating the position and orientation of objects in scenes typical for bin-picking. An automated system will rank teams on accuracy and efficiency.
OpenCV
Pedro Lopes
José Oramas
Alex Chan
lalmei
David Culley
GripNews
Adam Cook