Laura Leal-Taixé

research

∙ 09/16/2023

Staged Contact-Aware Global Human Motion Forecasting

Scene-aware global human motion forecasting is critical for manifold app...

0 Luca Scofano, et al. ∙

research

∙ 08/29/2023

NOVIS: A Case for End-to-End Near-Online Video Instance Segmentation

Until recently, the Video Instance Segmentation (VIS) community operated...

0 Tim Meinhardt, et al. ∙

research

∙ 06/20/2023

Data-Driven but Privacy-Conscious: Pedestrian Dataset De-identification via Full-Body Person Synthesis

The advent of data-driven technology solutions is accompanied by an incr...

9 Maxim Maximov, et al. ∙

research

∙ 04/23/2023

Walking Your LiDOG: A Journey Through Multiple Domains for LiDAR Semantic Segmentation

The ability to deploy robots that can operate safely in diverse environm...

2 Cristiano Saltori, et al. ∙

research

∙ 12/06/2022

Unifying Short and Long-Term Tracking with Graph Hierarchies

Tracking objects over long videos effectively means solving a spectrum o...

0 Orcun Cetintas, et al. ∙

research

∙ 12/06/2022

G-MSM: Unsupervised Multi-Shape Matching with Graph-based Affinity Priors

We present G-MSM (Graph-based Multi-Shape Matching), a novel unsupervise...

0 Marvin Eisenberger, et al. ∙

research

∙ 10/19/2022

Learning to Discover and Detect Objects

We tackle the problem of novel class discovery, detection, and localizat...

0 Vladimir Fomenko, et al. ∙

research

∙ 10/14/2022

Quo Vadis: Is Trajectory Forecasting the Key Towards Long-Term Multi-Object Tracking?

Recent developments in monocular multi-object tracking have been very su...

0 Patrick Dendorfer, et al. ∙

research

∙ 10/11/2022

The Unreasonable Effectiveness of Fully-Connected Layers for Low-Data Regimes

Convolutional neural networks were the standard for solving many compute...

0 Peter Kocsis, et al. ∙

research

∙ 09/29/2022

DirectTracker: 3D Multi-Object Tracking Using Direct Image Alignment and Photometric Bundle Adjustment

Direct methods have shown excellent performance in the applications of v...

0 Mariia Gladkova, et al. ∙

research

∙ 08/03/2022

PolarMOT: How Far Can Geometric Relations Take Us in 3D Multi-Object Tracking?

Most (3D) multi-object tracking methods rely on appearance-based cues fo...

0 Aleksandr Kim, et al. ∙

research

∙ 07/22/2022

DeVIS: Making Deformable Transformers Work for Video Instance Segmentation

Video Instance Segmentation (VIS) jointly tackles multi-object detection...

0 Adrià Caelles, et al. ∙

research

∙ 07/15/2022

Multi-Object Tracking and Segmentation via Neural Message Passing

Graphs offer a natural way to formulate Multiple Object Tracking (MOT) a...

0 Guillem Brasó, et al. ∙

research

∙ 06/09/2022

Simple Cues Lead to a Strong Multi-Object Tracker

For a long time, the most common paradigm in Multi-Object Tracking was t...

0 Jenny Seidenschwarz, et al. ∙

research

∙ 05/13/2022

A Unified Framework for Implicit Sinkhorn Differentiation

The Sinkhorn operator has recently experienced a surge of popularity in ...

3 Marvin Eisenberger, et al. ∙

research

∙ 03/30/2022

Forecasting from LiDAR via Future Object Detection

Object detection and forecasting are fundamental components of embodied ...

0 Neehar Peri, et al. ∙

research

∙ 03/28/2022

Text2Pos: Text-to-Point-Cloud Cross-Modal Localization

Natural language-based communication with mobile devices and home applia...

0 Manuel Kolmet, et al. ∙

research

∙ 03/24/2022

Is Geometry Enough for Matching in Visual Localization?

In this paper, we propose to go beyond the well-established approach to ...

0 Qunjie Zhou, et al. ∙

research

∙ 03/23/2022

DynamicEarthNet: Daily Multi-Spectral Satellite Dataset for Semantic Change Segmentation

Earth observation is a fundamental tool for monitoring the evolution of ...

13 Aysim Toker, et al. ∙

research

∙ 10/11/2021

The Center of Attention: Center-Keypoint Grouping via Attention for Multi-Person Pose Estimation

We introduce CenterGroup, an attention-based framework to estimate human...

0 Guillem Brasó, et al. ∙

research

∙ 08/21/2021

MOTSynth: How Can Synthetic Data Help Pedestrian Detection and Tracking?

Deep learning-based methods for video pedestrian detection and tracking ...

3 Matteo Fabbri, et al. ∙

research

∙ 08/20/2021

MG-GAN: A Multi-Generator Model Preventing Out-of-Distribution Samples in Pedestrian Trajectory Prediction

Pedestrian trajectory prediction is challenging due to its uncertain and...

6 Patrick Dendorfer, et al. ∙

research

∙ 08/06/2021

(Just) A Spoonful of Refinements Helps the Registration Error Go Down

We tackle data-driven 3D point cloud registration. Given point correspon...

8 Sérgio Agostinho, et al. ∙

research

∙ 06/22/2021

Towards Reducing Labeling Cost in Deep Object Detection

Deep neural networks have reached very high accuracy on object detection...

7 Ismail Elezi, et al. ∙

research

∙ 06/17/2021

DeepLab2: A TensorFlow Library for Deep Labeling

DeepLab2 is a TensorFlow library for deep labeling, aiming to provide a ...

0 Mark Weber, et al. ∙

research

∙ 06/17/2021

The 2021 Image Similarity Dataset and Challenge

This paper introduces a new benchmark for large-scale image similarity d...

23 Matthijs Douze, et al. ∙

research

∙ 04/29/2021

EagerMOT: 3D Multi-Object Tracking via Sensor Fusion

Multi-object tracking (MOT) enables mobile robots to perform well-inform...

0 Aleksandr Kim, et al. ∙

research

∙ 03/11/2021

Coming Down to Earth: Satellite-to-Street View Synthesis for Geo-Localization

The goal of cross-view image based geo-localization is to determine the ...

0 Aysim Toker, et al. ∙

research

∙ 03/08/2021

Vision-Based Mobile Robotics Obstacle Avoidance With Deep Reinforcement Learning

Obstacle avoidance is a fundamental and challenging problem for autonomo...

7 Patrick Wenzel, et al. ∙

research

∙ 02/24/2021

4D Panoptic LiDAR Segmentation

Temporal semantic scene understanding is critical for self-driving cars ...

0 Mehmet Aygün, et al. ∙

research

∙ 02/23/2021

STEP: Segmenting and Tracking Every Pixel

In this paper, we tackle video panoptic segmentation, a task that requir...

0 Mark Weber, et al. ∙

research

∙ 02/15/2021

Learning Intra-Batch Connections for Deep Metric Learning

The goal of metric learning is to learn a function that maps samples to ...

14 Jenny Seidenschwarz, et al. ∙

research

∙ 01/07/2021

TrackFormer: Multi-Object Tracking with Transformers

We present TrackFormer, an end-to-end multi-object tracking and segmenta...

16 Tim Meinhardt, et al. ∙

research

∙ 12/03/2020

Patch2Pix: Epipolar-Guided Pixel-Level Correspondences

Deep learning has been applied to a classical matching pipeline which ty...

5 Qunjie Zhou, et al. ∙

research

∙ 12/03/2020

Make One-Shot Video Object Segmentation Efficient Again

Video object segmentation (VOS) describes the task of segmenting a set o...

0 Tim Meinhardt, et al. ∙

research

∙ 10/28/2020

Deep Shells: Unsupervised Shape Correspondence with Optimal Transport

We propose a novel unsupervised learning approach to 3D shape correspond...

0 Marvin Eisenberger, et al. ∙

research

∙ 10/27/2020

Ice Monitoring in Swiss Lakes from Optical Satellites and Webcams using Machine Learning

Continuous observation of climate indicators, such as trends in lake fre...

8 Manu Tom, et al. ∙

research

∙ 10/15/2020

MOTChallenge: A Benchmark for Single-camera Multiple Target Tracking

Standardized benchmarks have been crucial in pushing the performance of ...

4 Patrick Dendorfer, et al. ∙

research

∙ 10/02/2020

Goal-GAN: Multimodal Trajectory Prediction Based on Goal Position Estimation

In this paper, we present Goal-GAN, an interpretable and end-to-end trai...

14 Patrick Dendorfer, et al. ∙

research

∙ 09/16/2020

HOTA: A Higher Order Metric for Evaluating Multi-Object Tracking

Multi-Object Tracking (MOT) has been notoriously difficult to evaluate. ...

15 Jonathon Luiten, et al. ∙

research

∙ 08/26/2020

Making a Case for 3D Convolutions for Object Segmentation in Videos

The task of object segmentation in videos is usually accomplished by pro...

9 Sabarinath Mahadevan, et al. ∙

research

∙ 05/19/2020

Focus on defocus: bridging the synthetic to real domain gap for depth estimation

Data-driven depth estimation methods struggle with the generalization ou...

4 Maxim Maximov, et al. ∙

research

∙ 05/19/2020

CIAGAN: Conditional Identity Anonymization Generative Adversarial Networks

The unprecedented increase in the usage of computer vision technology in...

15 Maxim Maximov, et al. ∙

research

∙ 05/07/2020

Planning from Images with Deep Latent Gaussian Process Dynamics

Planning is a powerful approach to control problems with known environme...

12 Nathanael Bosch, et al. ∙

research

∙ 03/19/2020

MOT20: A benchmark for multi object tracking in crowded scenes

Standardized benchmarks are crucial for the majority of computer vision ...

17 Patrick Dendorfer, et al. ∙

research

∙ 03/18/2020

STEm-Seg: Spatio-temporal Embeddings for Instance Segmentation in Videos

Existing methods for instance segmentation in videos typically involve m...

6 Ali Athar, et al. ∙

research

∙ 02/18/2020

Lake Ice Monitoring with Webcams and Crowd-Sourced Images

Lake ice is a strong climate indicator and has been recognised as part o...

3 Rajanie Prabha, et al. ∙

research

∙ 01/30/2020

Learn to Predict Sets Using Feed-Forward Neural Networks

This paper addresses the task of set prediction using deep feed-forward ...

30 Hamid Rezatofighi, et al. ∙

research

∙ 12/16/2019

Learning a Neural Solver for Multiple Object Tracking

Graphs offer a natural way to formulate Multiple Object Tracking (MOT) w...

15 Guillem Brasó, et al. ∙

research

∙ 12/11/2019

HistoNet: Predicting size histograms of object instances

We propose to predict histograms of object sizes in crowded scenes direc...

11 Kishan Sharma, et al. ∙

Laura Leal-Taixé

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