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20232026
most citedSpectralGaussians: Semantic, spectral 3D Gaussian splatting for multi-spectral scene representation, visualization and analysis

1 citations · 1 across the 7 of their papers we have counts for

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cs.CV2026

Curating Synthetic Data for Task-Specific Visual Perception

Saptarshi Neil Sinha, Paul Julius Kühn, Michael Weinmann

Synthetic data are most valuable where general-purpose datasets cannot provide the domain-specific priors a task requires, and where manual annotation is expensive, imprecise, or i…

cs.CV2026

SpectralCTGaussians: Projection-Domain Reconstruction and Basis Material Decomposition for Spectral CT using 3D Gaussian Splatting

Reinout Vos, Saptarshi Neil Sinha, Michael Weinmann

Spectral computed tomography (CT) extends conventional CT by measuring attenuation across multiple energy channels, allowing improved modeling of physical X-ray interactions and en…

cs.CV2026

AgenticCADedit: A Stateful, Tool-Mediated Agentic Approach to Multimodal 3D CAD Editing

Saptarshi Neil Sinha, Mika Silvan Goschke, Paul Julius Kühn +2

Computer-aided design is central to industrial manufacturing, and much of a designer's daily work consists of editing existing models from multimodal requests involving speech, ske…

cs.CV2026

TinyDETR-Pose: Towards End-to-End Real-Time Single-Stage 6DoF Object Pose Estimation with Lightweight Transformers

Paul Julius Kühn, Duc Anh Nguyen, Saptarshi Neil Sinha +2

Real-time 6DoF object pose estimation on resource-constrained hardware remains challenging, as accurate correspondence-based and refinement pipelines typically rely on non-differen…

cs.CV2026

ScratchSim: A Procedural Synthetic Data Pipeline for Surface Scratch Detection

Paul Julius Kühn, Saptarshi Neil Sinha, Tiago Kleist +3

While automated defect detection such as the detection of surface scratched is an important aspect in industrial quality control, the scarcity of annotated defect data make this ta…

cs.CV2026

Optimizing Multi-Modal Models for Image-Based Shape Retrieval: The Role of Pre-Alignment and Hard Contrastive Learning

Paul Julius Kühn, Cedric Spengler, Michael Weinmann +2

Image-based shape retrieval (IBSR) aims to retrieve 3D models from a database given a query image, hence addressing a classical task in computer vision, computer graphics, and robo…

cs.CV2025

6D Strawberry Pose Estimation: Real-time and Edge AI Solutions Using Purely Synthetic Training Data

Saptarshi Neil Sinha, Julius Kühn, Mika Silvan Goschke +1

Automated and selective harvesting of fruits has become an important area of research, particularly due to challenges such as high costs and a shortage of seasonal labor in advance…

cs.CV2025

Neural Restoration of Greening Defects in Historical Autochrome Photographs Based on Purely Synthetic Data

Saptarshi Neil Sinha, P. Julius Kuehn, Johannes Koppe +2

The preservation of early visual arts, particularly color photographs, is challenged by deterioration caused by aging and improper storage, leading to issues like blurring, scratch…

cs.CV2024★ 1 cited

SpectralGaussians: Semantic, spectral 3D Gaussian splatting for multi-spectral scene representation, visualization and analysis

Saptarshi Neil Sinha, Holger Graf, Michael Weinmann

We propose a novel cross-spectral rendering framework based on 3D Gaussian Splatting (3DGS) that generates realistic and semantically meaningful splats from registered multi-view s…

cs.CV2023

RANRAC: Robust Neural Scene Representations via Random Ray Consensus

Benno Buschmann, Andreea Dogaru, Elmar Eisemann +2

Learning-based scene representations such as neural radiance fields or light field networks, that rely on fitting a scene model to image observations, commonly encounter challenges…