Publications associées à Enhancing Hand and Object Detection for Monitoring Patients with Upper-Limb Impairment: A Study on the Impact of Input Size in Foundation Models

Publications associées (9)

Scaling the Modalities in Multimodal Foundation Models

Having a single neural network to handle a wide and varied range of tasks and modalities has been a long-standing goal. Such a model brings notable advantages, such as test-time computational efficiency, modality fusion, and reduced model size. Our goal in ...

EPFL2025

Programming Light Propagation for Efficient Artificial Intelligence

Ilker Oguz

Contemporary artificial intelligence (AI) models' exponentially growing complexity translates to their expanding skill sets. They can create language or image content mimicking human creativity and understanding, becoming indispensable tools in education, ...

EPFL2025

From Preprocessing to Evaluation: The Role of External Knowledge in Advancing Language Models and Machine Translation

Georgios Vernikos

Machine translation (MT) systems and language models (LMs) have demonstrated impressive performance in recent years, driven by advances in architecture, algorithms, and the scaling of parameters and training data. Despite the ability of these models to int ...

EPFL2025

GigaPose: Fast and Robust Novel Object Pose Estimation via One Correspondence

Mathieu Salzmann

We present GigaPose, a fast, robust, and accurate method for CAD-based novel object pose estimation in RGB images. GigaPose first leverages discriminative "templates", rendered images of the CAD models, to recover the out-of-plane rotation and then uses pa ...

IEEE2024

ISR-LLM: Iterative Self-Refined Large Language Model for Long-Horizon Sequential Task Planning

Kunpeng Yao

Motivated by the substantial achievements of Large Language Models (LLMs) in the field of natural language processing, recent research has commenced investigations into the application of LLMs for complex, long-horizon sequential task planning challenges i ...

Institute of Electrical and Electronics Engineers Inc.2024

Graph-based regularization of inverse problems in imaging

Mattia Rossi

As of today, the extension of the human visual capabilities to machines remains both a cornerstone and an open challenge in the attempt to develop intelligent systems. On the one hand, the development of more and more sophisticated imaging devices, capable ...

EPFL2020

A Neuro-Inspired Computational Model for a Visually Guided Robotic Lamprey Using Frame and Event Based Cameras

Auke Ijspeert, Alessandro Crespi, Mehmet Hasan Mutlu, Simon Lukas Hauser, Alexandre Bernardino, Mohammadreza Bayat

The computational load associated with computer vision is often prohibitive, and limits the capacity for on-board image analysis in compact mobile robots. Replicating the kind of feature detection and neural processing that animals excel at remains a chall ...

2020

Vision-Based Unmanned Aerial Vehicle Detection and Tracking for Sense and Avoid Systems

Krishna Raj Sapkota, Pascal Fua, Denis Gillet, Alcherio Martinoli, Vincent Lepetit, Steven Adriaan Roelofsen, Artem Rozantsev

We propose an approach for on-line detection of small Unmanned Aerial Vehicles (UAVs) and estimation of their relative positions and velocities in the 3D environment from a single moving camera in the context of sense and avoid systems. This problem is cha ...

Ieee2016

Optimistic Concurrency with OPTIK

Rachid Guerraoui, Vasileios Trigonakis

We introduce OPTIK, a new practical design pattern for designing and implementing fast and scalable concurrent data structures. OPTIK relies on the commonly-used technique of version numbers for detecting conflicting concurrent operations. We show how to i ...

ACM Press2016