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Gonzalo Ferrer

19 accepted papers

2026

CADFS: A Big CAD Program Dataset and Framework for Computer-Aided Design with Large Language Models

Vladislav Pyatov, Gleb Bobrovskikh, Saveliy Galochkin, Nikita Boldyrev, Oleg Voynov, Alexander Filippov +3
CVPR 2026

We introduce CADFS, a data-centric framework that enables large vision-language models to generate complex CAD design histories. Existing generative CAD systems are restricted to sketch-extrude operations due to simplified representations and limited datasets. We address this by introducing a Featur

Cited by 3Source ↗code ↗Scholar ↗
2024

GSLoc: Visual Localization with 3D Gaussian Splatting

Kazii Botashev, Vladislav Pyatov, Gonzalo Ferrer, Stamatios Lefkimmiatis
IROS 2024poster

We present GSLoc: a new visual localization method that performs dense camera alignment using 3D Gaussian Splatting as a map representation of the scene. GSLoc backpropagates pose gradients over the rendering pipeline to align the rendered and target images, while it adopts a coarse-to-fine strategy…

Cited by 5Source ↗Scholar ↗
2023

Analytical Jacobian Approximation for Direct Optimization of a Trajectory of Interpolated Poses on SE(3)

Kazii Botashev, Gonzalo Ferrer
IROS 2023poster

This paper relates to time-continuous trajectory representation using direct linear interpolation on SE(3). Our approach focuses on a novel analytical Jacobian approximation of a sequence of linearly interpolated poses on SE(3). This paper shows a derivation of the proposed analytical Jacobian using…

Cited by 1Source ↗Scholar ↗
2023

EVOLIN Benchmark: Evaluation of Line Detection and Association

Kirill Ivanov, Gonzalo Ferrer, Anastasiia Kornilova
IROS 2023poster

Lines are interesting geometrical features commonly seen in indoor and urban environments. There is missing a complete benchmark where one can evaluate lines from a sequential stream of images in all its stages: Line detection, Line Association and Pose error. To do so, we present a complete and exh…

Cited by 3Source ↗code ↗Scholar ↗
2023

NeSS-ST: Detecting Good and Stable Keypoints with a Neural Stability Score and the Shi-Tomasi detector

Konstantin Pakulev, Alexander Vakhitov, Gonzalo Ferrer
ICCV 2023poster

Learning a feature point detector presents a challenge both due to the ambiguity of the definition of a keypoint and, correspondingly, the need for specially prepared ground truth labels for such points. In our work, we address both of these issues by utilizing a combination of a hand-crafted Shi-To…

Cited by 4PDF ↗code ↗Scholar ↗
2022

Conditioned Human Trajectory Prediction using Iterative Attention Blocks

Aleksey Postnikov, Aleksander Gamayunov, Gonzalo Ferrer
ICRA 2022poster

Human motion prediction is key to understand social environments, with direct applications in robotics, surveil-lance, etc. We present a simple yet effective pedestrian trajectory prediction model aimed at pedestrians' positions prediction in urban-like environments conditioned by the environment: m…

Cited by 6Source ↗Scholar ↗
2022

EVOPS Benchmark: Evaluation of Plane Segmentation from RGBD and LiDAR Data

Anastasiia Kornilova, Dmitrii Iarosh, Denis Kukushkin, Nikolai Goncharov, Pavel Mokeev, Arthur Saliou +1
IROS 2022poster

This paper provides the EVOPS dataset for plane segmentation from 3D data, both from RGBD images and LiDAR point clouds. We have designed two annotation methodologies (RGBD and LiDAR) running on well-known and widely-used datasets for SLAM evaluation and we have provided a complete set of benchmarki…

Cited by 6Source ↗Scholar ↗
2022

SmartPortraits: Depth Powered Handheld Smartphone Dataset of Human Portraits for State Estimation, Reconstruction and Synthesis

Anastasiia Kornilova, Marsel Faizullin, Konstantin Pakulev, Andrey Sadkov, Denis Kukushkin, Azat Akhmetyanov +3
CVPR 2022poster

We present a dataset of 1000 video sequences of human portraits recorded in real and uncontrolled conditions by using a handheld smartphone accompanied by an external high-quality depth camera. The collected dataset contains 200 people captured in different poses and locations and its main purpose i…

Cited by 9PDF ↗Scholar ↗
2021

CovarianceNet: Conditional Generative Model for Correct Covariance Prediction in Human Motion Prediction

Aleksey Postnikov, Aleksander Gamayunov, Gonzalo Ferrer
IROS 2021poster

The correct characterization of uncertainty when predicting human motion is equally important as the accuracy of this prediction. We present a new method to correctly predict the uncertainty associated with the predicted distribution of future trajectories. Our approach, CovariaceNet, is based on a…

Cited by 5Source ↗Scholar ↗
2020

TT-TSDF: Memory-Efficient TSDF with Low-Rank Tensor Train Decomposition

Alexey I. Boyko, Mikhail P. Matrosov, Ivan V. Oseledets, Dzmitry Tsetserukou, Gonzalo Ferrer
IROS 2020poster

In this paper we apply the low-rank Tensor Train decomposition for compression and operations on 3D objects and scenes represented by volumetric distance functions. Our study shows that not only it allows for a very efficient compression of the high-resolution TSDF maps (up to three orders of magnit…

Cited by 9Source ↗Scholar ↗
2018

Backprop-MPDM: Faster Risk-Aware Policy Evaluation Through Efficient Gradient Optimization

Dhanvin Mehta, Gonzalo Ferrer, Edwin Olson
ICRA 2018poster

In Multi-Policy Decision-Making (MPDM), many computationally-expensive forward simulations are performed in order to predict the performance of a set of candidate policies. In risk-aware formulations of MPDM, only the worst outcomes affect the decision making process, and efficiently finding these i…

Cited by 17Source ↗Scholar ↗
2018

C-MPDM: Continuously-Parameterized Risk-Aware MPDM by Quickly Discovering Contextual Policies

Dhanvin Mehta, Gonzalo Ferrer, Edwin Olson
IROS 2018poster

Risk-aware Multi-Policy Decision Making (MPDM)is a powerful framework for reliable navigation in a dynamic social environment where rather than evaluating individual trajectories, a “library” of policies (reactive controllers)is evaluated by anticipating potentially dangerous future outcomes using a…

Cited by 3Source ↗Scholar ↗
2017

On-line adaptive side-by-side human robot companion in dynamic urban environments

Ely Repiso, Gonzalo Ferrer, Alberto Sanfeliu
IROS 2017poster

This paper presents an adaptive side-by-side human-robot companion approach for navigation in urban dynamic environments, based on the anticipative kinodynamic planning. The adaptive means that the robot is capable of adjusting its motion to the behavior of the person being accompanied. Our main obj…

Cited by 32Source ↗Scholar ↗
2016

Autonomous navigation in dynamic social environments using Multi-Policy Decision Making

Dhanvin Mehta, Gonzalo Ferrer, Edwin Olson
IROS 2016poster

In dynamic environments crowded with people, robot motion planning becomes difficult due to the complex and tightly-coupled interactions between agents. Trajectory planning methods, supported by models of typical human behavior and personal space, often produce reasonable behavior. However, they do…

Cited by 117Source ↗Scholar ↗