Angélique Loesch

5 papers · 2022–2024 · 3 venues · across top CS/AI venues

Authors are matched by name, so researchers who share a name ("Yang Liu", "Wei Wang") appear as a single profile and their paper counts, venues and achievements are combined. How identity is handled.

Achievements

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🌍 Conference Polyglot · Bronze 🌉 Interdisciplinary Bridge · Bronze 🗺️ Taxonomy Completionist (12) ❓ The Questioner

Venues

WACV (3) ECCV (1) ICLR (1)

Top co-authors

Amaury Habrard (3) Romaric Audigier (3) Quentin Bouniot (3) Hichem Sahbi (2) Florian Chabot (2) Rémi Marsal (2) William Grolleau (1) Ievgen Redko (1)

Research topics

Computer Vision (4) Machine Learning (4) Analysis (4) Learning Types · Machine Learning (4) Artificial Intelligence (2) Deep Learning (1) Core AI (1) Learning Paradigms (1) Learning Types · Deep Learning (1)

Keywords

object detection (2) contrastive learning (1) semi-supervised learning (1) few-shot learning (1) unsupervised pretraining (1) uncertainty quantification (1) self-supervised learning (1) depth estimation (1) monocular depth estimation (1) optical flow estimation (1) probabilistic model (1) autonomous vehicle (1) video frame (1) student-teacher architecture (1) depth prediction (1) object proposal (1) photometric loss (1) brightness change (1) deformable detr (1) unsupervised learning (1)

Papers

MonoProb: Self-Supervised Monocular Depth Estimation With Interpretable Uncertainty WACV 2024 BrightFlow: Brightness-Change-Aware Unsupervised Learning of Optical Flow WACV 2023 Proposal-Contrastive Pretraining for Object Detection from Fewer Data ICLR 2023 Towards Few-Annotation Learning for Object Detection: Are Transformer-Based Models More Efficient? WACV 2023 Improving Few-Shot Learning through Multi-task Representation Learning Theory ECCV 2022