6 citations · 14 across the 15 of their papers we have counts for
22 papers
Long Time No See: Benchmarking VLMs for Out-of-Sight Spatiotemporal Reasoning in Egocentric Videos
Fangzhou Ma, Ivo Alexander Ban, Eren Homburg +5
Real-world AI systems must reason about objects that are no longer visible: an AR assistant guiding a user back to an object used earlier, a household robot retrieving an item some…
Multimodal Floorplan Encoding: Learning Dense Modality-Invariant Representations
Xavier Anadón, Rémi Pautrat, Rui Wang
Floorplans arise in many forms, from vector CAD drawings to raster renderings and sensor-derived density maps. This heterogeneity makes it difficult to build learning systems that…
Pixel-wise Planarity for High-Precision Monocular Plane Segmentation
Ahmetcan Yavuz, Alpay Ozkan, Rémi Pautrat +2
Plane segmentation from a single RGB image remains challenging due to imprecise region grouping and geometrically inconsistent supervision, often leading to over-segmentation and f…
Stable and Scalable Bundle Adjustment of Holistic 3D Structures
Shaohui Liu, Rémi Pautrat, Daniel Barath +3
Bundle Adjustment (BA) is a cornerstone of 3D computer vision and has benefited from decades of advances in sparse optimization and numerical methods. It was originally developed f…
Unified and Efficient Point-Line Local Features
François Costa, Raphael Kreft, Eckhard Goedeke +6
Multi-view computer vision pipelines typically rely on accurate sparse keypoints and robust descriptors. While incorporating line features has shown clear benefits for matching and…
PolyLayout: Multi-room Manhattan Layout Estimation
Gustav Hanning, Shaohui Liu, Rémi Pautrat +3
Estimating room layouts from multi-view imagery is a core task for indoor scene understanding. Existing methods are typically limited either by poor generalization to new datasets…
CoPE-VideoLM: Leveraging Codec Primitives For Efficient Video Language Modeling
Sayan Deb Sarkar, Rémi Pautrat, Ondrej Miksik +4
Video Language Models (VideoLMs) enable AI systems to understand temporal dynamics in videos. To fit within the maximum context window constraint, current methods use keyframe samp…
LightGlueStick: a Fast and Robust Glue for Joint Point-Line Matching
Aidyn Ubingazhibov, Rémi Pautrat, Iago Suárez +3
Lines and points are complementary local features, whose combination has proven effective for applications such as SLAM and Structure-from-Motion. The backbone of these pipelines a…
Relative Pose Estimation through Affine Corrections of Monocular Depth Priors
Yifan Yu, Shaohui Liu, Rémi Pautrat +2
Monocular depth estimation (MDE) models have undergone significant advancements over recent years. Many MDE models aim to predict affine-invariant relative depth from monocular ima…
Robust Incremental Structure-from-Motion with Hybrid Features
Shaohui Liu, Yidan Gao, Tianyi Zhang +4
Structure-from-Motion (SfM) has become a ubiquitous tool for camera calibration and scene reconstruction with many downstream applications in computer vision and beyond. While the…
3D Neural Edge Reconstruction
Lei Li, Songyou Peng, Zehao Yu +4
Real-world objects and environments are predominantly composed of edge features, including straight lines and curves. Such edges are crucial elements for various applications, such…
Long-Term Invariant Local Features via Implicit Cross-Domain Correspondences
Zador Pataki, Mohammad Altillawi, Menelaos Kanakis +5
Modern learning-based visual feature extraction networks perform well in intra-domain localization, however, their performance significantly declines when image pairs are captured…
Handbook on Leveraging Lines for Two-View Relative Pose Estimation
Petr Hruby, Shaohui Liu, Rémi Pautrat +2
We propose an approach for estimating the relative pose between calibrated image pairs by jointly exploiting points, lines, and their coincidences in a hybrid manner. We investigat…
Vanishing Point Estimation in Uncalibrated Images with Prior Gravity Direction
Rémi Pautrat, Shaohui Liu, Petr Hruby +2
We tackle the problem of estimating a Manhattan frame, i.e. three orthogonal vanishing points, and the unknown focal length of the camera, leveraging a prior vertical direction. Th…
GlueStick: Robust Image Matching by Sticking Points and Lines Together
Rémi Pautrat, Iago Suárez, Yifan Yu +2
Line segments are powerful features complementary to points. They offer structural cues, robust to drastic viewpoint and illumination changes, and can be present even in texture-le…
3D Line Mapping Revisited
Shaohui Liu, Yifan Yu, Rémi Pautrat +2
In contrast to sparse keypoints, a handful of line segments can concisely encode the high-level scene layout, as they often delineate the main structural elements. In addition to o…
DeepLSD: Line Segment Detection and Refinement with Deep Image Gradients
Rémi Pautrat, Daniel Barath, Viktor Larsson +2
Line segments are ubiquitous in our human-made world and are increasingly used in vision tasks. They are complementary to feature points thanks to their spatial extent and the stru…
Controllable Data Augmentation Through Deep Relighting
George Chogovadze, Rémi Pautrat, Marc Pollefeys
At the heart of the success of deep learning is the quality of the data. Through data augmentation, one can train models with better generalization capabilities and thus achieve gr…
SOLD2: Self-supervised Occlusion-aware Line Description and Detection
Rémi Pautrat, Juan-Ting Lin, Viktor Larsson +2
Compared to feature point detection and description, detecting and matching line segments offer additional challenges. Yet, line features represent a promising complement to points…
Online Invariance Selection for Local Feature Descriptors
Rémi Pautrat, Viktor Larsson, Martin R. Oswald +1
To be invariant, or not to be invariant: that is the question formulated in this work about local descriptors. A limitation of current feature descriptors is the trade-off between…
Object Finding in Cluttered Scenes Using Interactive Perception
Tonci Novkovic, Remi Pautrat, Fadri Furrer +3
Object finding in clutter is a skill that requires perception of the environment and in many cases physical interaction. In robotics, interactive perception defines a set of algori…
Bayesian Optimization with Automatic Prior Selection for Data-Efficient Direct Policy Search
Rémi Pautrat, Konstantinos Chatzilygeroudis, Jean-Baptiste Mouret
One of the most interesting features of Bayesian optimization for direct policy search is that it can leverage priors (e.g., from simulation or from previous tasks) to accelerate l…