26 citations · 91 across the 25 of their papers we have counts for
29 papers
S-MUSt3R: Sliding Multi-view 3D Reconstruction
Leonid Antsfeld, Boris Chidlovskii, Yohann Cabon +2
The recent paradigm shift in 3D vision led to the rise of foundation models with remarkable capabilities in 3D perception from uncalibrated images. However, extending these models…
PanSt3R: Multi-view Consistent Panoptic Segmentation
Lojze Zust, Yohann Cabon, Juliette Marrie +4
Panoptic segmentation of 3D scenes, involving the segmentation and classification of object instances in a dense 3D reconstruction of a scene, is a challenging problem, especially…
Reasoning in visual navigation of end-to-end trained agents: a dynamical systems approach
Steeven Janny, Hervé Poirier, Leonid Antsfeld +6
Progress in Embodied AI has made it possible for end-to-end-trained agents to navigate in photo-realistic environments with high-level reasoning and zero-shot or language-condition…
MUSt3R: Multi-view Network for Stereo 3D Reconstruction
Yohann Cabon, Lucas Stoffl, Leonid Antsfeld +4
DUSt3R introduced a novel paradigm in geometric computer vision by proposing a model that can provide dense and unconstrained Stereo 3D Reconstruction of arbitrary image collection…
3D-Consistent Image Inpainting with Diffusion Models
Leonid Antsfeld, Boris Chidlovskii
We address the problem of 3D inconsistency of image inpainting based on diffusion models. We propose a generative model using image pairs that belong to the same scene. To achieve…
Self-supervised Pretraining and Finetuning for Monocular Depth and Visual Odometry
Boris Chidlovskii, Leonid Antsfeld
For the task of simultaneous monocular depth and visual odometry estimation, we propose learning self-supervised transformer-based models in two steps. Our first step consists in a…
Zero-BEV: Zero-shot Projection of Any First-Person Modality to BEV Maps
Gianluca Monaci, Leonid Antsfeld, Boris Chidlovskii +1
Bird's-eye view (BEV) maps are an important geometrically structured representation widely used in robotics, in particular self-driving vehicles and terrestrial robots. Existing al…
Learning to navigate efficiently and precisely in real environments
Guillaume Bono, Hervé Poirier, Leonid Antsfeld +3
In the context of autonomous navigation of terrestrial robots, the creation of realistic models for agent dynamics and sensing is a widespread habit in the robotics literature and…
Multi-Object Navigation in real environments using hybrid policies
Assem Sadek, Guillaume Bono, Boris Chidlovskii +2
Navigation has been classically solved in robotics through the combination of SLAM and planning. More recently, beyond waypoint planning, problems involving significant components…
DUSt3R: Geometric 3D Vision Made Easy
Shuzhe Wang, Vincent Leroy, Yohann Cabon +2
Multi-view stereo reconstruction (MVS) in the wild requires to first estimate the camera parameters e.g. intrinsic and extrinsic parameters. These are usually tedious and cumbersom…
End-to-End (Instance)-Image Goal Navigation through Correspondence as an Emergent Phenomenon
Guillaume Bono, Leonid Antsfeld, Boris Chidlovskii +2
Most recent work in goal oriented visual navigation resorts to large-scale machine learning in simulated environments. The main challenge lies in learning compact representations g…
Learning whom to trust in navigation: dynamically switching between classical and neural planning
Sombit Dey, Assem Sadek, Gianluca Monaci +2
Navigation of terrestrial robots is typically addressed either with localization and mapping (SLAM) followed by classical planning on the dynamically created maps, or by machine le…
Semantic Image Segmentation: Two Decades of Research
Gabriela Csurka, Riccardo Volpi, Boris Chidlovskii
Semantic image segmentation (SiS) plays a fundamental role in a broad variety of computer vision applications, providing key information for the global understanding of an image. T…
CroCo v2: Improved Cross-view Completion Pre-training for Stereo Matching and Optical Flow
Philippe Weinzaepfel, Thomas Lucas, Vincent Leroy +7
Despite impressive performance for high-level downstream tasks, self-supervised pre-training methods have not yet fully delivered on dense geometric vision tasks such as stereo mat…
CroCo: Self-Supervised Pre-training for 3D Vision Tasks by Cross-View Completion
Philippe Weinzaepfel, Vincent Leroy, Thomas Lucas +7
Masked Image Modeling (MIM) has recently been established as a potent pre-training paradigm. A pretext task is constructed by masking patches in an input image, and this masked con…
Unsupervised Domain Adaptation for Semantic Image Segmentation: a Comprehensive Survey
Gabriela Csurka, Riccardo Volpi, Boris Chidlovskii
Semantic segmentation plays a fundamental role in a broad variety of computer vision applications, providing key information for the global understanding of an image. Yet, the stat…
An in-depth experimental study of sensor usage and visual reasoning of robots navigating in real environments
Assem Sadek, Guillaume Bono, Boris Chidlovskii +1
Visual navigation by mobile robots is classically tackled through SLAM plus optimal planning, and more recently through end-to-end training of policies implemented as deep networks…
Learning From Long-Tailed Data With Noisy Labels
Shyamgopal Karthik, Jérome Revaud, Boris Chidlovskii
Class imbalance and noisy labels are the norm rather than the exception in many large-scale classification datasets. Nevertheless, most works in machine learning typically assume b…
Magnetic Field Sensing for Pedestrian and Robot Indoor Positioning
Leonid Antsfeld, Boris Chidlovskii
In this paper we address the problem of indoor localization using magnetic field data in two setups, when data is collected by (i) human-held mobile phone and (ii) by localization…
Universal Domain Adaptation in Ordinal Regression
Boris Chidlovskii, Assem Sadek, Christian Wolf
We address the problem of universal domain adaptation (UDA) in ordinal regression (OR), which attempts to solve classification problems in which labels are not independent, but fol…
Learning Synthetic to Real Transfer for Localization and Navigational Tasks
Maxime Pietrantoni, Boris Chidlovskii, Tomi Silander
Autonomous navigation consists in an agent being able to navigate without human intervention or supervision, it affects both high level planning and low level control. Navigation i…
Deep Smartphone Sensors-WiFi Fusion for Indoor Positioning and Tracking
Leonid Antsfeld, Boris Chidlovskii, Emilio Sansano-Sansano
We address the indoor localization problem, where the goal is to predict user's trajectory from the data collected by their smartphone, using inertial sensors such as accelerometer…
Adversarial Transfer of Pose Estimation Regression
Boris Chidlovskii, Assem Sadek
We address the problem of camera pose estimation in visual localization. Current regression-based methods for pose estimation are trained and evaluated scene-wise. They depend on t…
Self-Supervised Attention Learning for Depth and Ego-motion Estimation
Assem Sadek, Boris Chidlovskii
We address the problem of depth and ego-motion estimation from image sequences. Recent advances in the domain propose to train a deep learning model for both tasks using image reco…