David Stutz's Projects
ArXiv'18 implementation of amortized maximum likelihood (AML) for high-quality, weakly-supervised shape completion.
Simple Python scripts to clean up and flatten ArXiv LaTeX submissions.
A curated list of awesome computer vision resources
Bachelor thesis "Superpixel Segmentation using Depth Information", including a thorough comparison of several state-of-the-art superpixel algorithms.
Fork of the Light Random Spray Retinex Algorithm as discussed in [1].
Fork of the "Color Sparrow" color constancy algorithm described in [1].
Minimal but elegant file upload button for Twitter Bootstrap and IE 7/8/9 support.
JQuery multiselect plugin based on Twitter Bootstrap.
Password strength meter based on Twitter Bootstrap and Password Score.
Blender/bpy utilities for paper-ready visualizations of meshes, point clouds and occupancy grids.
Some tools and examples for pyCaffe including LMDB I/O, custom Python layers and monitoring training error and loss.
Data used for examples in daidstutz/caffe-tools.
BBClone plugin for CMSimple.
A simple CMSimple theme based on Twitter Bootstrap.
CMSimple elFinder filebrowser.
CMSimple elRTE WYSIWYG editor.
CMSimple theme of my personal webpage.
CMSimple plugin for managing and publishing news.
CMSimple plugin for creating different kinds of sliders and galleries.
CMSimple plugin for creating youtube video galleries.
Provides color names and HTML/RGB mappings in various output formats.
Implementation of Confidence-Calibrated Adversarial Training (CCAT).
CVIU 2018 paper "Superpixels: An Evaluation of the State-of-the-Art" - https://arxiv.org/abs/1612.01601.
CVPR 2018 paper "Learning 3D Shape Completion from Laser Scan Data with Weak Supervision".
CVPR 2019 paper "Disentangling Adversarial Robustness and Generalization".
Topological sort using d3.js.
CVPR'18 implementation of (deterministic) amortized maximum likelihood (AML) for weakly-supervised shape completion.
Personal README.
CVPR'19 experiments with (on-manifold) adversarial examples.
Extended version of the Berkeley Segmentation Benchmark [1] used for evaluation in [2].