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08/29/2023
Classification robustness to common optical aberrations
Computer vision using deep neural networks (DNNs) has brought about semi...
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08/21/2023
Local Spherical Harmonics Improve Skeleton-Based Hand Action Recognition
Hand action recognition is essential. Communication, human-robot interac...
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07/25/2023
On the unreasonable vulnerability of transformers for image restoration – and an easy fix
Following their success in visual recognition tasks, Vision Transformers...
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07/20/2023
Divide Bind Your Attention for Improved Generative Semantic Nursing
Emerging large-scale text-to-image generative models, e.g., Stable Diffu...
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07/18/2023
An Evaluation of Zero-Cost Proxies – from Neural Architecture Performance to Model Robustness
Zero-cost proxies are nowadays frequently studied and used to search for...
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07/02/2023
Intra- Extra-Source Exemplar-Based Style Synthesis for Improved Domain Generalization
The generalization with respect to domain shifts, as they frequently app...
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06/11/2023
Neural Architecture Design and Robustness: A Dataset
Deep learning models have proven to be successful in a wide range of mac...
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06/11/2023
Happy People – Image Synthesis as Black-Box Optimization Problem in the Discrete Latent Space of Deep Generative Models
In recent years, optimization in the learned latent space of deep genera...
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04/28/2023
Differentiable Sensor Layouts for End-to-End Learning of Task-Specific Camera Parameters
The success of deep learning is frequently described as the ability to t...
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03/20/2023
FullFormer: Generating Shapes Inside Shapes
Implicit generative models have been widely employed to model 3D data an...
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02/04/2023
CosPGD: a unified white-box adversarial attack for pixel-wise prediction tasks
While neural networks allow highly accurate predictions in many tasks, t...
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10/18/2022
Intra-Source Style Augmentation for Improved Domain Generalization
The generalization with respect to domain shifts, as they frequently app...
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06/15/2022
SP-ViT: Learning 2D Spatial Priors for Vision Transformers
Recently, transformers have shown great potential in image classificatio...
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04/04/2022
Learning to solve Minimum Cost Multicuts efficiently using Edge-Weighted Graph Convolutional Neural Networks
The minimum cost multicut problem is the NP-hard/APX-hard combinatorial ...
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03/16/2022
Learning Where To Look – Generative NAS is Surprisingly Efficient
The efficient, automated search for well-performing neural architectures...
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12/10/2021
Optimizing Edge Detection for Image Segmentation with Multicut Penalties
The Minimum Cost Multicut Problem (MP) is a popular way for obtaining a ...
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08/12/2021
DARTS for Inverse Problems: a Study on Hyperparameter Sensitivity
Differentiable architecture search (DARTS) is a widely researched tool f...
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05/29/2021
Beyond the Spectrum: Detecting Deepfakes via Re-Synthesis
The rapid advances in deep generative models over the past years have le...
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05/16/2021
Uncertainty in Minimum Cost Multicuts for Image and Motion Segmentation
The minimum cost lifted multicut approach has proven practically good pe...
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03/31/2021
Multi-Class Multi-Instance Count Conditioned Adversarial Image Generation
Image generation has rapidly evolved in recent years. Modern architectur...
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03/04/2021
SpectralDefense: Detecting Adversarial Attacks on CNNs in the Fourier Domain
Despite the success of convolutional neural networks (CNNs) in many comp...
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12/05/2020
Spectral Distribution aware Image Generation
Recent advances in deep generative models for photo-realistic images hav...
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10/19/2020
Neural Architecture Performance Prediction Using Graph Neural Networks
In computer vision research, the process of automating architecture engi...
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10/09/2020
Smooth Variational Graph Embeddings for Efficient Neural Architecture Search
In this paper, we propose an approach to neural architecture search (NAS...
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08/22/2020
NAS-Bench-301 and the Case for Surrogate Benchmarks for Neural Architecture Search
Neural Architecture Search (NAS) is a logical next step in the automatic...
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08/18/2020
Self-supervised Sparse to Dense Motion Segmentation
Observable motion in videos can give rise to the definition of objects m...
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07/06/2020
Learning Embeddings for Image Clustering: An Empirical Study of Triplet Loss Approaches
In this work, we evaluate two different image clustering objectives, k-m...
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03/03/2020
Watch your Up-Convolution: CNN Based Generative Deep Neural Networks are Failing to Reproduce Spectral Distributions
Generative convolutional deep neural networks, e.g. popular GAN architec...
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02/04/2020
Unsupervised Multiple Person Tracking using AutoEncoder-Based Lifted Multicuts
Multiple Object Tracking (MOT) is a long-standing task in computer visio...
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12/11/2019
A Variational-Sequential Graph Autoencoder for Neural Architecture Performance Prediction
In computer vision research, the process of automating architecture engi...
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11/02/2019
Unmasking DeepFakes with simple Features
Deep generative models have recently achieved impressive results for man...
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10/05/2019
Object Segmentation Tracking from Generic Video Cues
We propose a light-weight variational framework for online tracking of o...
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02/15/2019
Massively Parallel Benders Decomposition for Correlation Clustering
We tackle the problem of graph partitioning for image segmentation using...
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08/06/2018
Occlusions, Motion and Depth Boundaries with a Generic Network for Disparity, Optical Flow or Scene Flow Estimation
Occlusions play an important role in disparity and optical flow estimati...
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09/06/2017
Learning Dilation Factors for Semantic Segmentation of Street Scenes
Contextual information is crucial for semantic segmentation. However, fi...
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04/06/2017
Higher-Order Minimum Cost Lifted Multicuts for Motion Segmentation
Most state-of-the-art motion segmentation algorithms draw their potentia...
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12/06/2016
FlowNet 2.0: Evolution of Optical Flow Estimation with Deep Networks
The FlowNet demonstrated that optical flow estimation can be cast as a l...
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06/08/2016
Point-wise mutual information-based video segmentation with high temporal consistency
In this paper, we tackle the problem of temporally consistent boundary d...
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04/08/2016
STD2P: RGBD Semantic Segmentation Using Spatio-Temporal Data-Driven Pooling
We propose a novel superpixel-based multi-view convolutional neural netw...
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05/26/2015
