168 citations · 241 across the 6 of their papers we have counts for
7 papers
Toward Foundation Models for Earth Monitoring: Proposal for a Climate Change Benchmark
Alexandre Lacoste, Evan David Sherwin, Hannah Kerner +9
Recent progress in self-supervision shows that pre-training large neural networks on vast amounts of unsupervised data can lead to impressive increases in generalisation for downst…
A Survey of Self-Supervised and Few-Shot Object Detection
Gabriel Huang, Issam Laradji, David Vazquez +2
Labeling data is often expensive and time-consuming, especially for tasks such as object detection and instance segmentation, which require dense labeling of the image. While few-s…
SSR: Semi-supervised Soft Rasterizer for single-view 2D to 3D Reconstruction
Issam Laradji, Pau Rodríguez, David Vazquez +1
Recent work has made significant progress in learning object meshes with weak supervision. Soft Rasterization methods have achieved accurate 3D reconstruction from 2D images with v…
Slanted Stixels: Representing San Francisco's Steepest Streets
Daniel Hernandez-Juarez, Lukas Schneider, Antonio Espinosa +5
In this work we present a novel compact scene representation based on Stixels that infers geometric and semantic information. Our approach overcomes the previous rather restrictive…
The One Hundred Layers Tiramisu: Fully Convolutional DenseNets for Semantic Segmentation
Simon Jégou, Michal Drozdzal, David Vazquez +2
State-of-the-art approaches for semantic image segmentation are built on Convolutional Neural Networks (CNNs). The typical segmentation architecture is composed of (a) a downsampli…
Embedded real-time stereo estimation via Semi-Global Matching on the GPU
Daniel Hernandez-Juarez, Alejandro Chacón, Antonio Espinosa +3
Dense, robust and real-time computation of depth information from stereo-camera systems is a computationally demanding requirement for robotics, advanced driver assistance systems…