Search Results for "robust"

...The design emphasizes consistent geometric reasoning: outputs from one head (e.g., correspondences or tracks) reinforce others (e.g., pose or depth), making the system more robust to challenging viewpoints and textures. The repo provides inference pipelines to estimate geometry from monocular inputs, stereo pairs, or brief sequences, together with evaluation harnesses for common geometry benchmarks. Training utilities highlight data curation and augmentations that preserve geometric cues while improving generalization across scenes and cameras.

ImageAI is an easy-to-use Computer Vision Python library that empowers developers to easily integrate state-of-the-art Artificial Intelligence features into their new and existing applications and systems. It is used by thousands of developers, students, researchers, tutors and experts in corporate organizations around the world. You will find features supported, links to official documentation as well as articles on ImageAI. ImageAI is widely used around the world by professionals,...

...The project is now available for the iCub platform to work on YARP [https://github.com/stino78/vergence-control/][1] The algorithm works on the top of a distributed representation of binocular disparity supplied by a population of binocular energy-model neural units. The project allows a robust control and adaptive binocular coordination for different robot stereo platforms. Reference publications: Gibaldi, A., Vanegas, M., Canessa, A., & Sabatini, S. P. (2017). A portable bio-inspired architecture for efficient robotic vergence control. International Journal of Computer Vision,. Gibaldi, A., Canessa, A., Chessa, M., Sabatini, S. ...

ECO (Efficient Convolution Operators for Tracking) is a high-performance object tracking algorithm developed by Martin Danelljan and collaborators. It is based on discriminative correlation filters and designed to handle appearance changes, occlusions, and scale variations in visual object tracking tasks. The code provides a MATLAB implementation of the ECO and ECO-HC (high-speed) variants and was one of the top performers on multiple visual tracking benchmarks.

reacTIVision is a computer vision framework for the fast and robust tracking of markers attached on physical objects, and the creation of multi-touch surfaces. It was designed for the rapid development of table-based tangible user interfaces.

NetVLAD is a deep learning-based image descriptor framework developed by Relja Arandjelović for place recognition and image retrieval. It extends standard CNNs with a trainable VLAD (Vector of Locally Aggregated Descriptors) layer to create compact, robust global descriptors from image features. This implementation includes training code and pretrained models using the Pittsburgh and Tokyo datasets.