Christian Rupprecht

research

∙ 07/14/2023

CoTracker: It is Better to Track Together

Methods for video motion prediction either estimate jointly the instanta...

0 Nikita Karaev, et al. ∙

research

∙ 06/27/2023

PoseDiffusion: Solving Pose Estimation via Diffusion-aided Bundle Adjustment

Camera pose estimation is a long-standing computer vision problem that t...

0 Jianyuan Wang, et al. ∙

research

∙ 06/15/2023

Diffusion Models for Zero-Shot Open-Vocabulary Segmentation

The variety of objects in the real world is nearly unlimited and is thus...

0 Laurynas Karazija, et al. ∙

research

∙ 06/13/2023

Viewset Diffusion: (0-)Image-Conditioned 3D Generative Models from 2D Data

We present Viewset Diffusion: a framework for training image-conditioned...

0 Stanislaw Szymanowicz, et al. ∙

research

∙ 05/03/2023

DynamicStereo: Consistent Dynamic Depth from Stereo Videos

We consider the problem of reconstructing a dynamic scene observed from ...

1 Nikita Karaev, et al. ∙

research

∙ 04/20/2023

Farm3D: Learning Articulated 3D Animals by Distilling 2D Diffusion

We present Farm3D, a method to learn category-specific 3D reconstructors...

0 Tomas Jakab, et al. ∙

research

∙ 04/13/2023

What does CLIP know about a red circle? Visual prompt engineering for VLMs

Large-scale Vision-Language Models, such as CLIP, learn powerful image-t...

0 Aleksandar Shtedritski, et al. ∙

research

∙ 04/06/2023

Continual Detection Transformer for Incremental Object Detection

Incremental object detection (IOD) aims to train an object detector in p...

0 Yaoyao Liu, et al. ∙

research

∙ 03/23/2023

Temperature Schedules for Self-Supervised Contrastive Methods on Long-Tail Data

Most approaches for self-supervised learning (SSL) are optimised on cura...

0 Anna Kukleva, et al. ∙

research

∙ 02/21/2023

PC^2: Projection-Conditioned Point Cloud Diffusion for Single-Image 3D Reconstruction

Reconstructing the 3D shape of an object from a single RGB image is a lo...

0 Luke Melas-Kyriazi, et al. ∙

research

∙ 02/21/2023

RealFusion: 360° Reconstruction of Any Object from a Single Image

We consider the problem of reconstructing a full 360 photographic model ...

0 Luke Melas-Kyriazi, et al. ∙

research

∙ 01/18/2023

Behind the Scenes: Density Fields for Single View Reconstruction

Inferring a meaningful geometric scene representation from a single imag...

0 Felix Wimbauer, et al. ∙

research

∙ 11/22/2022

MagicPony: Learning Articulated 3D Animals in the Wild

We consider the problem of learning a function that can estimate the 3D ...

0 Shangzhe Wu, et al. ∙

research

∙ 11/08/2022

Nondestructive thermographic detection of internal defects using pixel-pattern based laser excitation and photothermal super resolution reconstruction

In this work, we present a novel approach to photothermal super resoluti...

0 Julien Lecompagnon, et al. ∙

research

∙ 10/21/2022

Unsupervised Multi-object Segmentation by Predicting Probable Motion Patterns

We propose a new approach to learn to segment multiple image objects wit...

10 Laurynas Karazija, et al. ∙

research

∙ 10/19/2022

VTC: Improving Video-Text Retrieval with User Comments

Multi-modal retrieval is an important problem for many applications, suc...

2 Laura Hanu, et al. ∙

research

∙ 05/16/2022

Guess What Moves: Unsupervised Video and Image Segmentation by Anticipating Motion

Motion, measured via optical flow, provides a powerful cue to discover a...

15 Subhabrata Choudhury, et al. ∙

research

∙ 05/16/2022

Deep Spectral Methods: A Surprisingly Strong Baseline for Unsupervised Semantic Segmentation and Localization

Unsupervised localization and segmentation are long-standing computer vi...

0 Luke Melas-Kyriazi, et al. ∙

research

∙ 01/06/2022

De-rendering 3D Objects in the Wild

With increasing focus on augmented and virtual reality applications (XR)...

13 Felix Wimbauer, et al. ∙

research

∙ 11/19/2021

ClevrTex: A Texture-Rich Benchmark for Unsupervised Multi-Object Segmentation

There has been a recent surge in methods that aim to decompose and segme...

3 Laurynas Karazija, et al. ∙

research

∙ 11/11/2021

Unsupervised Part Discovery from Contrastive Reconstruction

The goal of self-supervised visual representation learning is to learn s...

5 Subhabrata Choudhury, et al. ∙

research

∙ 11/05/2021

The Curious Layperson: Fine-Grained Image Recognition without Expert Labels

Most of us are not experts in specific fields, such as ornithology. None...

9 Subhabrata Choudhury, et al. ∙

research

∙ 09/27/2021

PASS: An ImageNet replacement for self-supervised pretraining without humans

Computer vision has long relied on ImageNet and other large datasets of ...

7 Yuki M. Asano, et al. ∙

research

∙ 07/22/2021

DOVE: Learning Deformable 3D Objects by Watching Videos

Learning deformable 3D objects from 2D images is an extremely ill-posed ...

7 Shangzhe Wu, et al. ∙

research

∙ 05/17/2021

Finding an Unsupervised Image Segmenter in Each of Your Deep Generative Models

Recent research has shown that numerous human-interpretable directions e...

15 Luke Melas-Kyriazi, et al. ∙

research

∙ 03/31/2021

Neural Response Interpretation through the Lens of Critical Pathways

Is critical input information encoded in specific sparse pathways within...

12 Ashkan Khakzar, et al. ∙

research

∙ 06/24/2020

Labelling unlabelled videos from scratch with multi-modal self-supervision

A large part of the current success of deep learning lies in the effecti...

0 Yuki M. Asano, et al. ∙

research

∙ 04/07/2020

Semantic Image Manipulation Using Scene Graphs

Image manipulation can be considered a special case of image generation ...

1 Helisa Dhamo, et al. ∙

research

∙ 11/25/2019

Unsupervised Learning of Probably Symmetric Deformable 3D Objects from Images in the Wild

We propose a method to learn 3D deformable object categories from raw si...

26 Shangzhe Wu, et al. ∙

research

∙ 11/13/2019

Self-labelling via simultaneous clustering and representation learning

Combining clustering and representation learning is one of the most prom...

83 Yuki Markus Asano, et al. ∙

research

∙ 10/27/2019

Traffic4cast-Traffic Map Movie Forecasting – Team MIE-Lab

The goal of the IARAI competition traffic4cast was to predict the city-w...

0 Henry Martin, et al. ∙

research

∙ 08/25/2019

Towards Unsupervised Image Captioning with Shared Multimodal Embeddings

Understanding images without explicit supervision has become an importan...

6 Iro Laina, et al. ∙

research

∙ 06/04/2019

Photo-Geometric Autoencoding to Learn 3D Objects from Unlabelled Images

We show that generative models can be used to capture visual geometry co...

1 Shangzhe Wu, et al. ∙

research

∙ 04/30/2019

Surprising Effectiveness of Few-Image Unsupervised Feature Learning

State-of-the-art methods for unsupervised representation learning can tr...

18 Yuki M. Asano, et al. ∙

research

∙ 04/02/2019

Finding and Visualizing Weaknesses of Deep Reinforcement Learning Agents

As deep reinforcement learning driven by visual perception becomes more ...

0 Christian Rupprecht, et al. ∙

research

∙ 12/01/2018

Explaining the Ambiguity of Object Detection and 6D Pose from Visual Data

3D object detection and pose estimation from a single image are two inhe...

1 Fabian Manhardt, et al. ∙

research

∙ 11/02/2018

Dealing with Ambiguity in Robotic Grasping via Multiple Predictions

Humans excel in grasping and manipulating objects because of their life-...

8 Ghazal Ghazaei, et al. ∙

research

∙ 09/25/2018

Incremental Adversarial Learning for Optimal Path Planning

Path planning plays an essential role in many areas of robotics. Various...

0 Salvatore Virga, et al. ∙

research

∙ 04/20/2018

Understanding Regularization to Visualize Convolutional Neural Networks

Variational methods for revealing visual concepts learned by convolution...

0 Maximilian Baust, et al. ∙

research

∙ 03/30/2018

Guide Me: Interacting with Deep Networks

Interaction and collaboration between humans and intelligent machines ha...

2 Christian Rupprecht, et al. ∙

research

∙ 11/08/2017

Learning to Imagine Manipulation Goals for Robot Task Planning

Prospection is an important part of how humans come up with new task pla...

0 Chris Paxton, et al. ∙

research

∙ 06/14/2017

Learning without Prejudice: Avoiding Bias in Webly-Supervised Action Recognition

Webly-supervised learning has recently emerged as an alternative paradig...

0 Christian Rupprecht, et al. ∙

research

∙ 03/30/2017

Concurrent Segmentation and Localization for Tracking of Surgical Instruments

Real-time instrument tracking is a crucial requirement for various compu...

0 Iro Laina, et al. ∙

research

∙ 02/24/2017

Analyzing and Exploiting NARX Recurrent Neural Networks for Long-Term Dependencies

Recurrent neural networks (RNNs) have achieved state-of-the-art performa...

0 Robert DiPietro, et al. ∙

research

∙ 12/01/2016

Learning in an Uncertain World: Representing Ambiguity Through Multiple Hypotheses

Many prediction tasks contain uncertainty. In some cases, uncertainty is...

0 Christian Rupprecht, et al. ∙

research

∙ 09/20/2016

Hands-Free Segmentation of Medical Volumes via Binary Inputs

We propose a novel hands-free method to interactively segment 3D medical...

0 Florian Dubost, et al. ∙

research

∙ 06/24/2016

A Taxonomy and Library for Visualizing Learned Features in Convolutional Neural Networks

Over the last decade, Convolutional Neural Networks (CNN) saw a tremendo...

0 Felix Grün, et al. ∙

research

∙ 06/01/2016

Deeper Depth Prediction with Fully Convolutional Residual Networks

This paper addresses the problem of estimating the depth map of a scene ...

0 Iro Laina, et al. ∙

Christian Rupprecht

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