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09/16/2023
Staged Contact-Aware Global Human Motion Forecasting
Scene-aware global human motion forecasting is critical for manifold app...
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08/29/2023
NOVIS: A Case for End-to-End Near-Online Video Instance Segmentation
Until recently, the Video Instance Segmentation (VIS) community operated...
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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...
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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...
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12/06/2022
Unifying Short and Long-Term Tracking with Graph Hierarchies
Tracking objects over long videos effectively means solving a spectrum o...
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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...
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10/19/2022
Learning to Discover and Detect Objects
We tackle the problem of novel class discovery, detection, and localizat...
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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...
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10/11/2022
The Unreasonable Effectiveness of Fully-Connected Layers for Low-Data Regimes
Convolutional neural networks were the standard for solving many compute...
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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...
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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...
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07/22/2022
DeVIS: Making Deformable Transformers Work for Video Instance Segmentation
Video Instance Segmentation (VIS) jointly tackles multi-object detection...
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07/15/2022
Multi-Object Tracking and Segmentation via Neural Message Passing
Graphs offer a natural way to formulate Multiple Object Tracking (MOT) a...
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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...
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05/13/2022
A Unified Framework for Implicit Sinkhorn Differentiation
The Sinkhorn operator has recently experienced a surge of popularity in ...
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03/30/2022
Forecasting from LiDAR via Future Object Detection
Object detection and forecasting are fundamental components of embodied ...
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03/28/2022
Text2Pos: Text-to-Point-Cloud Cross-Modal Localization
Natural language-based communication with mobile devices and home applia...
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03/24/2022
Is Geometry Enough for Matching in Visual Localization?
In this paper, we propose to go beyond the well-established approach to ...
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03/23/2022
DynamicEarthNet: Daily Multi-Spectral Satellite Dataset for Semantic Change Segmentation
Earth observation is a fundamental tool for monitoring the evolution of ...
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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...
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08/21/2021
MOTSynth: How Can Synthetic Data Help Pedestrian Detection and Tracking?
Deep learning-based methods for video pedestrian detection and tracking ...
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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...
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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...
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06/22/2021
Towards Reducing Labeling Cost in Deep Object Detection
Deep neural networks have reached very high accuracy on object detection...
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06/17/2021
DeepLab2: A TensorFlow Library for Deep Labeling
DeepLab2 is a TensorFlow library for deep labeling, aiming to provide a ...
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06/17/2021
The 2021 Image Similarity Dataset and Challenge
This paper introduces a new benchmark for large-scale image similarity d...
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04/29/2021
EagerMOT: 3D Multi-Object Tracking via Sensor Fusion
Multi-object tracking (MOT) enables mobile robots to perform well-inform...
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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 ...
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03/08/2021
Vision-Based Mobile Robotics Obstacle Avoidance With Deep Reinforcement Learning
Obstacle avoidance is a fundamental and challenging problem for autonomo...
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02/24/2021
4D Panoptic LiDAR Segmentation
Temporal semantic scene understanding is critical for self-driving cars ...
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02/23/2021
STEP: Segmenting and Tracking Every Pixel
In this paper, we tackle video panoptic segmentation, a task that requir...
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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 ...
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01/07/2021
TrackFormer: Multi-Object Tracking with Transformers
We present TrackFormer, an end-to-end multi-object tracking and segmenta...
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12/03/2020
Patch2Pix: Epipolar-Guided Pixel-Level Correspondences
Deep learning has been applied to a classical matching pipeline which ty...
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12/03/2020
Make One-Shot Video Object Segmentation Efficient Again
Video object segmentation (VOS) describes the task of segmenting a set o...
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10/28/2020
Deep Shells: Unsupervised Shape Correspondence with Optimal Transport
We propose a novel unsupervised learning approach to 3D shape correspond...
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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...
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10/15/2020
MOTChallenge: A Benchmark for Single-camera Multiple Target Tracking
Standardized benchmarks have been crucial in pushing the performance of ...
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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...
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09/16/2020
HOTA: A Higher Order Metric for Evaluating Multi-Object Tracking
Multi-Object Tracking (MOT) has been notoriously difficult to evaluate. ...
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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...
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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...
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05/19/2020
CIAGAN: Conditional Identity Anonymization Generative Adversarial Networks
The unprecedented increase in the usage of computer vision technology in...
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05/07/2020
Planning from Images with Deep Latent Gaussian Process Dynamics
Planning is a powerful approach to control problems with known environme...
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03/19/2020
MOT20: A benchmark for multi object tracking in crowded scenes
Standardized benchmarks are crucial for the majority of computer vision ...
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03/18/2020
STEm-Seg: Spatio-temporal Embeddings for Instance Segmentation in Videos
Existing methods for instance segmentation in videos typically involve m...
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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...
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01/30/2020
Learn to Predict Sets Using Feed-Forward Neural Networks
This paper addresses the task of set prediction using deep feed-forward ...
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12/16/2019
Learning a Neural Solver for Multiple Object Tracking
Graphs offer a natural way to formulate Multiple Object Tracking (MOT) w...
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12/11/2019
