18 citations · 21 across the 14 of their papers we have counts for
10 papers · 1 filter
How (Mis)calibrated is your Federated CLIP and what to do about it?
Mainak Singha, Masih Aminbeidokhti, Paolo Casari +3
Vision-language models (VLMs) such as CLIP are increasingly adapted across decentralized data silos, yet the reliability of their predictions under federated learning (FL) remains…
Infrared Object Detection with Ultra Small ConvNets: Is ImageNet Pretraining Still Useful?
Srikanth Muralidharan, Heitor R. Medeiros, Masih Aminbeidokhti +2
Many real-world applications require recognition models that are robust to different operational conditions and modalities, but at the same time run on small embedded devices, with…
CTA: Cross-Task Alignment for Better Test Time Training
Samuel Barbeau, Pedram Fekri, David Osowiechi +4
Deep learning models have demonstrated exceptional performance across a wide range of computer vision tasks. However, their performance often degrades significantly when faced with…
WiSE-OD: Benchmarking Robustness in Infrared Object Detection
Heitor R. Medeiros, Atif Belal, Masih Aminbeidokhti +2
Object detection (OD) in infrared (IR) imagery is critical for low-light and nighttime applications. However, the scarcity of large-scale IR datasets forces models to rely on weigh…
Distilling Specialized Orders for Visual Generation
Rishav Pramanik, Amin Sghaier, Masih Aminbeidokhti +6
Autoregressive (AR) image generators are becoming increasingly popular due to their ability to produce high-quality images and their scalability. Typical AR models are locked onto…
Source-Free Domain Adaptation for YOLO Object Detection
Simon Varailhon, Masih Aminbeidokhti, Marco Pedersoli +1
Source-free domain adaptation (SFDA) is a challenging problem in object detection, where a pre-trained source model is adapted to a new target domain without using any source domai…
Modality Translation for Object Detection Adaptation Without Forgetting Prior Knowledge
Heitor Rapela Medeiros, Masih Aminbeidokhti, Fidel Guerrero Pena +3
A common practice in deep learning involves training large neural networks on massive datasets to achieve high accuracy across various domains and tasks. While this approach works…
HalluciDet: Hallucinating RGB Modality for Person Detection Through Privileged Information
Heitor Rapela Medeiros, Fidel A. Guerrero Pena, Masih Aminbeidokhti +3
A powerful way to adapt a visual recognition model to a new domain is through image translation. However, common image translation approaches only focus on generating data from the…
Re-basin via implicit Sinkhorn differentiation
Fidel A. Guerrero Peña, Heitor Rapela Medeiros, Thomas Dubail +3
The recent emergence of new algorithms for permuting models into functionally equivalent regions of the solution space has shed some light on the complexity of error surfaces, and…
Privacy-Preserving Person Detection Using Low-Resolution Infrared Cameras
Thomas Dubail, Fidel Alejandro Guerrero Peña, Heitor Rapela Medeiros +3
In intelligent building management, knowing the number of people and their location in a room are important for better control of its illumination, ventilation, and heating with re…