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Konrad Schindler

Papers
21

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Semantic Scholar
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21papers

Authored papers

21

Marigold: Affordable Adaptation of Diffusion-Based Image Generators for Image Analysis

arXiv 2025

2025

BRIGHT: A globally distributed multimodal building damage assessment dataset with very-high-resolution for all-weather disaster response

arXiv 2025

2025

LitePT: Lighter Yet Stronger Point Transformer

arXiv 2025

2025

StereoSpace: Depth-Free Synthesis of Stereo Geometry via End-to-End Diffusion in a Canonical Space

arXiv 2025

2025

VIST3A: Text-to-3D by Stitching a Multi-view Reconstruction Network to a Video Generator

arXiv 2025

2025

Marigold-DC: Zero-Shot Monocular Depth Completion with Guided Diffusion

arXiv 2024

2024

Video Depth without Video Models

CVPR 2025 1

2024

LoRA-Ensemble: Efficient Uncertainty Modelling for Self-attention Networks

arXiv 2024

2024

LoopSplat: Loop Closure by Registering 3D Gaussian Splats

arXiv 2024

2024

AGBD: A Global-scale Biomass Dataset

arXiv 2024

2024

StegoGAN: Leveraging Steganography for Non-Bijective Image-to-Image Translation

CVPR 2024 1

2024

Consistency^2: Consistent and Fast 3D Painting with Latent Consistency Models

arXiv 2024

2024

Neural Fields with Thermal Activations for Arbitrary-Scale Super-Resolution

arXiv 2023

2023

DGInStyle: Domain-Generalizable Semantic Segmentation with Image Diffusion Models and Stylized Semantic Control

arXiv 2023

2023

Breathing New Life into 3D Assets with Generative Repainting

arXiv 2023

2023

Towards accurate instance segmentation in large-scale LiDAR point clouds

arXiv 2023

2023

Automated forest inventory: analysis of high-density airborne LiDAR point clouds with 3D deep learning

arXiv 2023

2023

Connecting the Dots: Floorplan Reconstruction Using Two-Level Queries

CVPR 2023 1

2022

Deep Active Learning in Remote Sensing for data efficient Change Detection

arXiv 2020

2020

Towards Robust Monocular Depth Estimation: Mixing Datasets for Zero-shot Cross-dataset Transfer

arXiv 2019

2019

Super-resolution of Sentinel-2 images: Learning a globally applicable deep neural network

arXiv 2018

2018

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10

from 21 papers