output
20022026
most citedMethods for Interpreting and Understanding Deep Neural Networks

2.8k citations

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57 papers · 1 filter

cs.CV20261 cited

AI-based worker guidance in assembly and disassembly operations using multimodal ego/exo-centric data capture and structured task knowledge

Vivek Chavan, Jörg Krüger

Assembly and disassembly processes rely on expert knowledge that is difficult to document, reuse, and transfer. This paper presents a data-centric approach for extracting structure…

cs.CV2026

MobileMold: A Smartphone-Based Microscopy Dataset for Food Mold Detection

Dinh Nam Pham, Leonard Prokisch, Bennet Meyer +1

Smartphone clip-on microscopes turn everyday devices into low-cost, portable imaging systems that can even reveal fungal structures at the microscopic level, enabling mold inspecti…

cs.CV2026

HOT-POT: Optimal Transport for Sparse Stereo Matching

Antonin Clerc, Michael Quellmalz, Moritz Piening +3

Stereo vision between images faces a range of challenges, including occlusions, motion, and camera distortions, across applications in autonomous driving, robotics, and face analys…

cs.CV20257 cited

Seabed-Net: A multi-task network for joint bathymetry estimation and seabed classification from remote sensing imagery in shallow waters

Panagiotis Agrafiotis, Begüm Demir

Accurate, detailed, and regularly updated bathymetry, coupled with complex semantic content, is essential for under-mapped shallow-water environments facing increasing climatologic…

cs.CV2025

Geometry-Aware Video Inpainting for Joint Headset Occlusion Removal and Face Reconstruction in Social XR

Fatemeh Ghorbani Lohesara, Karen Eguiazarian, Sebastian Knorr

Head-mounted displays (HMDs) are essential for experiencing extended reality (XR) environments and observing virtual content. However, they obscure the upper part of the user's fac…

cs.CV20251 cited

Enhancing 3D point accuracy of laser scanner through multi-stage convolutional neural network for applications in construction

Qinyuan Fan, Clemens Gühmann

We propose a multi-stage convolutional neural network (MSCNN) based integrated method for reducing uncertainty of 3D point accuracy of lasar scanner (LS) in rough indoor rooms, pro…