research
∙
07/14/2023
CoTracker: It is Better to Track Together
Methods for video motion prediction either estimate jointly the instanta...
share
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...
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...
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...
research
∙
05/03/2023
DynamicStereo: Consistent Dynamic Depth from Stereo Videos
We consider the problem of reconstructing a dynamic scene observed from ...
research
∙
04/20/2023
Farm3D: Learning Articulated 3D Animals by Distilling 2D Diffusion
We present Farm3D, a method to learn category-specific 3D reconstructors...
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...
research
∙
04/06/2023
Continual Detection Transformer for Incremental Object Detection
Incremental object detection (IOD) aims to train an object detector in p...
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...
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...
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 ...
research
∙
01/18/2023
Behind the Scenes: Density Fields for Single View Reconstruction
Inferring a meaningful geometric scene representation from a single imag...
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 ...
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...
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...
research
∙
10/19/2022
VTC: Improving Video-Text Retrieval with User Comments
Multi-modal retrieval is an important problem for many applications, suc...
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...
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...
research
∙
01/06/2022
De-rendering 3D Objects in the Wild
With increasing focus on augmented and virtual reality applications (XR)...
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...
research
∙
11/11/2021
Unsupervised Part Discovery from Contrastive Reconstruction
The goal of self-supervised visual representation learning is to learn s...
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...
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 ...
research
∙
07/22/2021
DOVE: Learning Deformable 3D Objects by Watching Videos
Learning deformable 3D objects from 2D images is an extremely ill-posed ...
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...
research
∙
03/31/2021
Neural Response Interpretation through the Lens of Critical Pathways
Is critical input information encoded in specific sparse pathways within...
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...
research
∙
04/07/2020
Semantic Image Manipulation Using Scene Graphs
Image manipulation can be considered a special case of image generation ...
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...
research
∙
11/13/2019
Self-labelling via simultaneous clustering and representation learning
Combining clustering and representation learning is one of the most prom...
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...
research
∙
08/25/2019
Towards Unsupervised Image Captioning with Shared Multimodal Embeddings
Understanding images without explicit supervision has become an importan...
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...
research
∙
04/30/2019
Surprising Effectiveness of Few-Image Unsupervised Feature Learning
State-of-the-art methods for unsupervised representation learning can tr...
research
∙
04/02/2019
Finding and Visualizing Weaknesses of Deep Reinforcement Learning Agents
As deep reinforcement learning driven by visual perception becomes more ...
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...
research
∙
11/02/2018
Dealing with Ambiguity in Robotic Grasping via Multiple Predictions
Humans excel in grasping and manipulating objects because of their life-...
research
∙
09/25/2018
Incremental Adversarial Learning for Optimal Path Planning
Path planning plays an essential role in many areas of robotics. Various...
research
∙
04/20/2018
Understanding Regularization to Visualize Convolutional Neural Networks
Variational methods for revealing visual concepts learned by convolution...
research
∙
03/30/2018
Guide Me: Interacting with Deep Networks
Interaction and collaboration between humans and intelligent machines ha...
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...
research
∙
06/14/2017
Learning without Prejudice: Avoiding Bias in Webly-Supervised Action Recognition
Webly-supervised learning has recently emerged as an alternative paradig...
research
∙
03/30/2017
Concurrent Segmentation and Localization for Tracking of Surgical Instruments
Real-time instrument tracking is a crucial requirement for various compu...
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...
research
∙
12/01/2016
Learning in an Uncertain World: Representing Ambiguity Through Multiple Hypotheses
Many prediction tasks contain uncertainty. In some cases, uncertainty is...
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...
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...
research
∙
06/01/2016