b'Thomas Brox'

research

∙ 09/18/2023

Unsupervised Open-Vocabulary Object Localization in Videos

In this paper, we show that recent advances in video representation lear...

0 Ke Fan, et al. ∙

research

∙ 09/01/2023

Object-Centric Multiple Object Tracking

Unsupervised object-centric learning methods allow the partitioning of s...

0 Zixu Zhao, et al. ∙

research

∙ 05/25/2023

Anomaly Detection with Conditioned Denoising Diffusion Models

Reconstruction-based methods have struggled to achieve competitive perfo...

0 Arian Mousakhan, et al. ∙

research

∙ 02/08/2023

Revisiting Deep Active Learning for Semantic Segmentation

Active learning automatically selects samples for annotation from a data...

0 Sudhanshu Mittal, et al. ∙

research

∙ 11/23/2022

Open-vocabulary Attribute Detection

Vision-language modeling has enabled open-vocabulary tasks where predict...

0 Maria A. Bravo, et al. ∙

research

∙ 11/12/2022

Far Away in the Deep Space: Nearest-Neighbor-Based Dense Out-of-Distribution Detection

The key to out-of-distribution detection is density estimation of the in...

0 Silvio Galesso, et al. ∙

research

∙ 11/03/2022

Towards Discovering Neural Architectures from Scratch

The discovery of neural architectures from scratch is the long-standing ...

0 Simon Schrodi, et al. ∙

research

∙ 09/29/2022

Bridging the Gap to Real-World Object-Centric Learning

Humans naturally decompose their environment into entities at the approp...

38 Maximilian Seitzer, et al. ∙

research

∙ 09/18/2022

SF2SE3: Clustering Scene Flow into SE(3)-Motions via Proposal and Selection

We propose SF2SE3, a novel approach to estimate scene dynamics in form o...

0 Leonhard Sommer, et al. ∙

research

∙ 09/13/2022

A Benchmark and a Baseline for Robust Multi-view Depth Estimation

Recent deep learning approaches for multi-view depth estimation are empl...

15 Philipp Schröppel, et al. ∙

research

∙ 08/30/2022

Probing Contextual Diversity for Dense Out-of-Distribution Detection

Detection of out-of-distribution (OoD) samples in the context of image c...

0 Silvio Galesso, et al. ∙

research

∙ 07/27/2022

RobotIO: A Python Library for Robot Manipulation Experiments

Setting up robot environments to quickly test newly developed algorithms...

0 Lukas Hermann, et al. ∙

research

∙ 07/19/2022

Assaying Out-Of-Distribution Generalization in Transfer Learning

Since out-of-distribution generalization is a generally ill-posed proble...

6 Florian Wenzel, et al. ∙

research

∙ 07/11/2022

Unsupervised Semantic Segmentation with Self-supervised Object-centric Representations

In this paper, we show that recent advances in self-supervised feature l...

16 Andrii Zadaianchuk, et al. ∙

research

∙ 07/08/2022

Pixel-level Correspondence for Self-Supervised Learning from Video

While self-supervised learning has enabled effective representation lear...

1 Yash Sharma, et al. ∙

research

∙ 05/17/2022

Conditional Visual Servoing for Multi-Step Tasks

Visual Servoing has been effectively used to move a robot into specific ...

0 Sergio Izquierdo, et al. ∙

research

∙ 05/12/2022

Localized Vision-Language Matching for Open-vocabulary Object Detection

In this work, we propose an open-world object detection method that, bas...

11 Maria A. Bravo, et al. ∙

research

∙ 02/15/2022

Neural Architecture Search for Dense Prediction Tasks in Computer Vision

The success of deep learning in recent years has lead to a rising demand...

0 Thomas Elsken, et al. ∙

research

∙ 01/27/2022

Ranking Info Noise Contrastive Estimation: Boosting Contrastive Learning via Ranked Positives

This paper introduces Ranking Info Noise Contrastive Estimation (RINCE),...

7 David T. Hoffmann, et al. ∙

research

∙ 12/16/2021

Search for temporal cell segmentation robustness in phase-contrast microscopy videos

Studying cell morphology changes in time is critical to understanding ce...

6 Estibaliz Gómez-de-Mariscal, et al. ∙

research

∙ 10/13/2021

Unsupervised Object Learning via Common Fate

Learning generative object models from unlabelled videos is a long stand...

7 Matthias Tangemann, et al. ∙

research

∙ 10/11/2021

You Mostly Walk Alone: Analyzing Feature Attribution in Trajectory Prediction

Predicting the future trajectory of a moving agent can be easy when the ...

10 Osama Makansi, et al. ∙

research

∙ 09/30/2021

CrossCLR: Cross-modal Contrastive Learning For Multi-modal Video Representations

Contrastive learning allows us to flexibly define powerful losses by con...

1 Mohammadreza Zolfaghari, et al. ∙

research

∙ 07/09/2021

Multi-headed Neural Ensemble Search

Ensembles of CNN models trained with different seeds (also known as Deep...

0 Ashwin Raaghav Narayanan, et al. ∙

research

∙ 06/28/2021

Test-Time Adaptation to Distribution Shift by Confidence Maximization and Input Transformation

Deep neural networks often exhibit poor performance on data that is unli...

0 Chaithanya Kumar Mummadi, et al. ∙

research

∙ 06/15/2021

Towards Total Recall in Industrial Anomaly Detection

Being able to spot defective parts is a critical component in large-scal...

8 Karsten Roth, et al. ∙

research

∙ 06/08/2021

Contrastive Representation Learning for Hand Shape Estimation

This work presents improvements in monocular hand shape estimation by bu...

0 Christian Zimmermann, et al. ∙

research

∙ 06/01/2021

Semi-Supervised Disparity Estimation with Deep Feature Reconstruction

Despite the success of deep learning in disparity estimation, the domain...

0 Julia Guerrero-Viu, et al. ∙

research

∙ 04/29/2021

Pre-training of Deep RL Agents for Improved Learning under Domain Randomization

Visual domain randomization in simulated environments is a widely used m...

15 Artemij Amiranashvili, et al. ∙

research

∙ 04/01/2021

Fostering Generalization in Single-view 3D Reconstruction by Learning a Hierarchy of Local and Global Shape Priors

Single-view 3D object reconstruction has seen much progress, yet methods...

0 Jan Bechtold, et al. ∙

research

∙ 03/30/2021

What Causes Optical Flow Networks to be Vulnerable to Physical Adversarial Attacks

Recent work demonstrated the lack of robustness of optical flow networks...

0 Simon Schrodi, et al. ∙

research

∙ 03/30/2021

Improving robustness against common corruptions with frequency biased models

CNNs perform remarkably well when the training and test distributions ar...

3 Tonmoy Saikia, et al. ∙

research

∙ 03/23/2021

On Exposing the Challenging Long Tail in Future Prediction of Traffic Actors

Predicting the states of dynamic traffic actors into the future is impor...

0 Osama Makansi, et al. ∙

research

∙ 02/18/2021

Essentials for Class Incremental Learning

Contemporary neural networks are limited in their ability to learn from ...

0 Sudhanshu Mittal, et al. ∙

research

∙ 11/20/2020

Recovering the Imperfect: Cell Segmentation in the Presence of Dynamically Localized Proteins

Deploying off-the-shelf segmentation networks on biomedical data has bec...

3 Özgün Çiçek, et al. ∙

research

∙ 11/01/2020

COOT: Cooperative Hierarchical Transformer for Video-Text Representation Learning

Many real-world video-text tasks involve different levels of granularity...

0 Simon Ging, et al. ∙

research

∙ 07/19/2020

Beyond Single Stage Encoder-Decoder Networks: Deep Decoders for Semantic Image Segmentation

Single encoder-decoder methodologies for semantic segmentation are reach...

21 Gabriel L. Oliveira, et al. ∙

research

∙ 07/06/2020

Scaling Imitation Learning in Minecraft

Imitation learning is a powerful family of techniques for learning senso...

3 Artemij Amiranashvili, et al. ∙

research

∙ 07/01/2020

FlowControl: Optical Flow Based Visual Servoing

One-shot imitation is the vision of robot programming from a single demo...

0 Max Argus, et al. ∙

research

∙ 06/08/2020

Multimodal Future Localization and Emergence Prediction for Objects in Egocentric View with a Reachability Prior

In this paper, we investigate the problem of anticipating future dynamic...

9 Osama Makansi, et al. ∙

research

∙ 04/04/2020

Multi-Variate Temporal GAN for Large Scale Video Generation

In this paper, we present a network architecture for video generation th...

0 Andres Muñoz, et al. ∙

research

∙ 01/22/2020

Optimized Generic Feature Learning for Few-shot Classification across Domains

To learn models or features that generalize across tasks and domains is ...

18 Tonmoy Saikia, et al. ∙

research

∙ 12/11/2019

Parting with Illusions about Deep Active Learning

Active learning aims to reduce the high labeling cost involved in traini...

26 Sudhanshu Mittal, et al. ∙

research

∙ 10/17/2019

Adaptive Curriculum Generation from Demonstrations for Sim-to-Real Visuomotor Control

We propose Adaptive Curriculum Generation from Demonstrations (ACGD) for...

22 Lukas Hermann, et al. ∙

research

∙ 10/17/2019

Self-supervised 3D Shape and Viewpoint Estimation from Single Images for Robotics

We present a convolutional neural network for joint 3D shape prediction ...

27 Oier Mees, et al. ∙

research

∙ 10/04/2019

SELF: Learning to Filter Noisy Labels with Self-Ensembling

Deep neural networks (DNNs) have been shown to over-fit a dataset when b...

0 Duc Tam Nguyen, et al. ∙

research

∙ 09/28/2019

DeepUSPS: Deep Robust Unsupervised Saliency Prediction With Self-Supervision

Deep neural network (DNN) based salient object detection in images based...

13 Duc Tam Nguyen, et al. ∙

research

∙ 09/20/2019

Understanding and Robustifying Differentiable Architecture Search

Differentiable Architecture Search (DARTS) has attracted a lot of attent...

0 Arber Zela, et al. ∙

research

∙ 09/10/2019

FreiHAND: A Dataset for Markerless Capture of Hand Pose and Shape from Single RGB Images

Estimating 3D hand pose from single RGB images is a highly ambiguous pro...

16 Christian Zimmermann, et al. ∙

research

∙ 08/15/2019

Semi-Supervised Semantic Segmentation with High- and Low-level Consistency

The ability to understand visual information from limited labeled data i...

5 Sudhanshu Mittal, et al. ∙

Thomas Brox

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