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20232026
most citedReliability in Semantic Segmentation: Can We Use Synthetic Data?

2 citations · 2 across the 7 of their papers we have counts for

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cs.CV2026

RoMa-: What Feed-Forward 3D Models Know About Image Matching

David Nordström, Xinyue Zhang, Thibaut Loiseau +2

Learned image matching has experienced significant progress in recent years, culminating in robust and accurate matchers such as RoMa, whose robustness is often attributed to its u…

cs.CV2026

Revisiting Cross-View Completion: Self-Supervised Pre-Training via Reconstruction Error Comparison

Thibaut Loiseau, Guillaume Bourmaud, Vincent Lepetit

Self-supervised pre-training via cross-view completion learns strong features for 3D vision from co-visible regions of image pairs. However, the reference view provides little info…

cs.CV2026

PoM: A Linear-Time Replacement for Attention with the Polynomial Mixer

David Picard, Nicolas Dufour, Lucas Degeorge +14

This paper introduces the Polynomial Mixer (PoM), a novel token mixing mechanism with linear complexity that serves as a drop-in replacement for self-attention. PoM aggregates inpu…

cs.CV2025

Alligat0R: Pre-Training Through Co-Visibility Segmentation for Relative Camera Pose Regression

Thibaut Loiseau, Guillaume Bourmaud, Vincent Lepetit

Pre-training techniques have greatly advanced computer vision, with CroCo's cross-view completion approach yielding impressive results in tasks like 3D reconstruction and pose regr…

cs.CV2025

RUBIK: A Structured Benchmark for Image Matching across Geometric Challenges

Thibaut Loiseau, Guillaume Bourmaud

Camera pose estimation is crucial for many computer vision applications, yet existing benchmarks offer limited insight into method limitations across different geometric challenges…

cs.CV2023★ 2 cited

Reliability in Semantic Segmentation: Can We Use Synthetic Data?

Thibaut Loiseau, Tuan-Hung Vu, Mickael Chen +2

Assessing the robustness of perception models to covariate shifts and their ability to detect out-of-distribution (OOD) inputs is crucial for safety-critical applications such as a…