Publications de Sabine Süsstrunk

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Self-supervised learning (SSL) has the potential to ben- efit many applications, particularly those where manually annotating data is cumbersome. One such situation is the semantic segmentation of point clouds. In this context, ex- isting methods employ co ...

Camera spectral sensitivity functions relate scene radiance with captured RGB triplets. They are important for many computer vision tasks that use color information, such as multispectral imaging, color rendering, and color constancy. In this paper, we aim ...

Skin tone images, portraits in particular, are of tremendous importance in digital photography, but a number of factors, such as pigmentation irregularities (e.g., moles, freckles), irritation, roughness, or wrinkles can reduce their appeal. Moreover, such ...

Several studies have suggested that translation and convergence in a linear trichromatic color space lead to the perception of transparency, but other transformations, such as shear and rotation,do not. We have designed a psychophysical experiment to study thelimits of such systemic chromatic changes, adding categories such as different luminance levels and vector lengths. The number of our stimuli and the number of observations provide strong statistical support for D'Zmura's model. Our main results show t

Fixed location cameras, such as panoramic cameras or surveillance cameras, are very common. In images taken with these cameras, there will be changes in lighting and dynamic image content, but there will also be constant objects in the background. We propo ...

If multiple images of a scene are available instead of a single image, we can use the additional information conveyed by the set of images to generate a higher quality image. This can be done along multiple dimensions. Super-resolution algorithms use a set ...

The large capacity of neural networks enables them to learn complex functions. To avoid overfitting, networks however require a lot of training data that can be expensive and time-consuming to collect. A common practical approach to attenuate overfitting i ...

Dynamic textures are sequences of images showing temporal regularity, such as smoke, flames, flowing water, or moving grass. Despite being a multidimensional signal, existing models reshape the dynamic texture into a 2D signal for analysis. In this article ...

Dynamic textures are sequences of images showing temporal regularity. Examples can be found in videos representing smoke, flames, ocean waves, wind-shaken forests, etc. Dynamic texture modelling and synthesis has usually been done considering RGB color ima ...

The two classic image restoration tasks, demosaicing and super-resolution, have traditionally always been studied indepen- dently. That is sub-optimal as sequential processing, demosaic- ing and then super-resolution, may lead to amplification of ar- tifac ...

The degree of visibility of any kind of stimulus is largely determined by the background on which it is shown, a property commonly known as masking. Many psychophysical experiments have been carried out to date to understand masking of sinusoids or Gabor targets by similar maskers and by noise, and a variety of masking models have been proposed. However, these stimuli are artificial and quite simplistic compared to natural scene content. Masking models based on such experiments may not be accurate for more

Knowledge of lens specifications is important to identify the best lens for a given capture scenario and application. Lens manufacturers provide many specifications in their data sheets, and multiple initiatives for testing and comparing different lenses c ...

The Bradford chromatic adaptation transform, empirically derived by Lam, models illumination change. Specifically, it provides a means of mapping XYZs under a reference source to XYZs for a target light such that the corresponding XYZs produce the same perceived colour. One implication of the Bradford chromatic adaptation transform is that colour correction for illumination takes place not in cone space but rather in a ‘narrowed’ cone space. The Bradford sensors have their sensitivity more narrowly concent

We tested whether motion and configural complexity affect perceived transparency. A series of five coherent chromatic transformations in color space was applied across a figure: translation, convergence, shear, divergence and rotation. The stimuli consiste ...

Superpixels are becoming increasingly popular for use in computer vision applications. However, there are few algorithms that output a desired number of regular, compact superpixels with a low computational overhead. We introduce a novel algorithm that clusters pixels in the combined five-dimensional color and image plane space to efficiently generate compact, nearly uniform superpixels. The simplicity of our approach makes it extremely easy to use -- a lone parameter specifies the number of superpixels --

In this supplementary material, we present the details of the neural network architecture and training settings used in all our experiments. This holds for all experiments presented in the main paper as well as in this supplementary material. We also show the summary results of all of our 96 experiments (test accuracy, training cross-entropy loss, and regularization loss), sampled at 100 epoch intervals. We analyze these results for each of the benchmark datasets, namely MNIST, Fashion-MNIST and CIFAR10, an

We analyze whether Independant Component Analysis (ICA) is an appropriate tool for estimating spatial information in spatiochromatic mosaiced color images. In previous studies, ICA analysis of natural color scenes (Hoyer et al. 2000; Tailor et al., 2000; Wachtler et al., 2001; Lee et al. 2002) have shown the emergence of achromatic patterns that can be used for luminance estimation. However, these analysis are based on fully defined spatio-chromatic images, i.e. three or more chromatic values per pixel. In

Starting from a sample of a given size, texture synthesis algorithms are used to create larger texture images. A good algorithm produces synthesized textures that are pixelwise different but perceptually indistinguishable from the original image. The sample image should be chosen ensuring that it contains a number of pattern repetitions sufficient to produce valuable synthesis results. Since textures can be characterized by patterns of different dimensions, this must be done in an adaptive way. In this arti

Developing an augmented reality (AR) system involves multiple algorithms such as image fusion, camera synchronization and calibration, and brightness control, each of them having diverse variants. This abundance of features, while beneficial in nature, is ...

We propose NEMTO, the first end-to-end neural render- ing pipeline to model 3D transparent objects with complex geometry and unknown indices of refraction. Commonly used appearance modeling such as the Disney BSDF model cannot accurately address this challenging problem due to the complex light paths bending through refractions and the strong dependency of surface appearance on illumina- tion. With 2D images of the transparent object as input, our method is capable of high-quality novel view and re- lightin

Sabine Süsstrunk

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Spatiotemporal Self-supervised Learning for Point Clouds in the Wild

What is the Space of Spectral Sensitivity Functions for Digital Color Cameras?

Combining visible and near-infrared images for realistic skin smoothing

Study of Systematic Chromatic Changes in Color Space to Model Color Transparency

Illuminant retrieval for fixed location cameras

Multidimensional image enhancement from a set of unregistered differently exposed images

AL2: Progressive Activation Loss for Learning General Representations in Classification Neural Networks

Dynamic Texture Analysis and Synthesis using Tensor Decomposition

Dynamic Texture Synthesis: Compact Models Based on Luminance -Chrominance Color Representation

Deep Residual Network for Joint Demosaicing and Super- Resolution

Visibility of noise in natural images

AAM: An Assessment Metric of Axial Chromatic Aberration

Spectral Sharpening and the Bradford Transform

Effects of Motion and Configural Complexity on Color Transparency Perception

SLIC Superpixels

Supplementary Material - AL2: Progressive Activation Loss for Learning General Representations in Classification Neural Networks

Spatio-chromatic ICA of a Mosaiced Color Image

Adapting the Sample Size in Texture Synthesis

AR in VR: Simulating Infrared Augmented Vision

NEMTO: Neural Environment Matting for Novel View and Relighting Synthesis of Transparent Objects