Paper Citation Record · LEDGER

Learning Densities in Feature Space for Reliable Segmentation of Indoor Scenes

As of 23 August 2026, this Paper Citation Record lists 28 of 28 outbound references and 0 inbound Pith citation observations for arXiv:1908.00448.

A citation records a reference. It does not transfer a finding from one paper to another.

pith.paper-citation-record.v1
1908.00448 v4

Coverage vector

measured 28 of 28 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-14T15:59:20.495062Z

measured 28 of 28 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-23T06:30:58.430688+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: cited_works

Reference resolution

28 of 28 outbound references displayed

verified exact0
verified fuzzy15
unresolved13
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 93d6a9a6-f5e6-4c75-866b-8b3a32b69d07 · outbound

This paper cites Dense object nets: Learn- ing dense visual object descriptors by and for robotic manipulation,.

Learning Densities in Feature Space for Reliable Segmentation of Indoor Scenes Dense object nets: Learn- ing dense visual object descriptors by and for robotic manipulation,

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T15:59:21.095525Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation c87887ff-b1ac-45b2-bbac-d9b838eabd68 · outbound

This paper cites A baseline for detecting misclassiﬁed and out-of-distribution examples in neural networks,.

Learning Densities in Feature Space for Reliable Segmentation of Indoor Scenes A baseline for detecting misclassiﬁed and out-of-distribution examples in neural networks,

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T15:59:21.080930Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 117f06d7-a56c-4488-9aaf-7c0992078046 · outbound

This paper cites A simple uniﬁed framework for detecting out-of-distribution samples and adversarial attacks,.

Learning Densities in Feature Space for Reliable Segmentation of Indoor Scenes A simple uniﬁed framework for detecting out-of-distribution samples and adversarial attacks,

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-14T15:59:20.390040Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8888cfbe-5e1b-4b40-91d1-4c5558471a2d · outbound

This paper cites WAIC, but Why? Generative Ensembles for Robust Anomaly Detection.

Learning Densities in Feature Space for Reliable Segmentation of Indoor Scenes WAIC, but Why? Generative Ensembles for Robust Anomaly Detection

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-14T15:59:20.394380Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ef40b17f-38d6-40cc-bbaa-ae93539c01f4 · outbound

This paper cites Towards open set deep networks,.

Learning Densities in Feature Space for Reliable Segmentation of Indoor Scenes Towards open set deep networks,

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T15:59:21.055387Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 92eb73d1-6c7c-48fb-ae73-791371799ed0 · outbound

This paper cites Safety for mobile robotic systems: A systematic mapping study from a software engineering perspective,.

Learning Densities in Feature Space for Reliable Segmentation of Indoor Scenes Safety for mobile robotic systems: A systematic mapping study from a software engineering perspective,

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T15:59:21.040928Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation c9ad5fb2-0846-4eab-a08f-eb39a685ed3e · outbound

This paper cites Mid-fusion: Octree-based object-level multi-instance dynamic slam,.

Learning Densities in Feature Space for Reliable Segmentation of Indoor Scenes Mid-fusion: Octree-based object-level multi-instance dynamic slam,

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T15:59:21.025810Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 4915cac3-6a6d-45e3-8212-fa4bd12dad1b · outbound

This paper cites Nice: Non-linear independent components estimation,.

Learning Densities in Feature Space for Reliable Segmentation of Indoor Scenes Nice: Non-linear independent components estimation,

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T15:59:21.010826Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 36f6f428-22e3-4a2f-a828-5210677a7ec9 · outbound

This paper cites Density estimation using real nvp,.

Learning Densities in Feature Space for Reliable Segmentation of Indoor Scenes Density estimation using real nvp,

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-14T15:59:20.417342Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5c7ae4af-6565-4f40-8a25-a55f37152e53 · outbound

This paper cites Glow: Generative ﬂow with invertible 1x1 convolutions,.

Learning Densities in Feature Space for Reliable Segmentation of Indoor Scenes Glow: Generative ﬂow with invertible 1x1 convolutions,

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T15:59:20.983131Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation a7e3a22c-1cc3-48d4-be2a-0ddd80c44748 · outbound

This paper cites The Fishyscapes Benchmark: Measuring Blind Spots in Semantic Segmentation.

Learning Densities in Feature Space for Reliable Segmentation of Indoor Scenes The Fishyscapes Benchmark: Measuring Blind Spots in Semantic Segmentation

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-14T15:59:20.425531Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 99057435-f007-4694-86a9-5e8dff576472 · outbound

This paper cites Fully convolutional networks for semantic segmentation,.

Learning Densities in Feature Space for Reliable Segmentation of Indoor Scenes Fully convolutional networks for semantic segmentation,

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T15:59:20.968515Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 4aea1946-3b09-4679-a97a-b07bc0592d0a · outbound

This paper cites Learning deconvolution network for semantic segmentation,.

Learning Densities in Feature Space for Reliable Segmentation of Indoor Scenes Learning deconvolution network for semantic segmentation,

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-14T15:59:20.434324Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 97c8d803-e893-4f04-bfc5-d9c946ede15a · outbound

This paper cites Mask r-cnn,.

Learning Densities in Feature Space for Reliable Segmentation of Indoor Scenes Mask r-cnn,

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-14T15:59:20.438284Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ece51f67-8af5-4796-a942-923be0c814fb · outbound

This paper cites Faster r-cnn: Towards real-time object detection with region proposal networks,.

Learning Densities in Feature Space for Reliable Segmentation of Indoor Scenes Faster r-cnn: Towards real-time object detection with region proposal networks,

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T15:59:20.931305Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation c482447e-b304-4402-9844-56cb7cd8639d · outbound

This paper cites V olumetric instance-aware semantic mapping and 3d object discovery,.

Learning Densities in Feature Space for Reliable Segmentation of Indoor Scenes V olumetric instance-aware semantic mapping and 3d object discovery,

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-14T15:59:20.445981Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0d3bcde5-7681-465a-a74e-cec1e7c72428 · outbound

This paper cites SegNet: A Deep Convolutional Encoder-Decoder Architecture for Robust Semantic Pixel-Wise Labelling.

Learning Densities in Feature Space for Reliable Segmentation of Indoor Scenes SegNet: A Deep Convolutional Encoder-Decoder Architecture for Robust Semantic Pixel-Wise Labelling

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-14T15:59:20.449790Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 17e93f79-6c5e-41c4-9ea6-9367d44193b3 · outbound

This paper cites Real-time foreground–background segmentation using codebook model,.

Learning Densities in Feature Space for Reliable Segmentation of Indoor Scenes Real-time foreground–background segmentation using codebook model,

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T15:59:20.866984Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 1b8d4653-78c9-49c1-99c4-3b137579244b · outbound

This paper cites Efﬁcient video object co- localization with co-saliency activated tracklets,.

Learning Densities in Feature Space for Reliable Segmentation of Indoor Scenes Efﬁcient video object co- localization with co-saliency activated tracklets,

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T15:59:20.850337Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 904c54b3-ef66-45da-85be-c5f8a685d0a7 · outbound

This paper cites Uncertainty in deep learning,.

Learning Densities in Feature Space for Reliable Segmentation of Indoor Scenes Uncertainty in deep learning,

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T15:59:20.835196Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation ce338f25-82d0-46d2-b9ed-d00ceeee6c28 · outbound

This paper cites What uncertainties do we need in bayesian deep learning for computer vision?.

Learning Densities in Feature Space for Reliable Segmentation of Indoor Scenes What uncertainties do we need in bayesian deep learning for computer vision?

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T15:59:20.796608Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 42728a17-22be-474e-9a07-cc684b10cfec · outbound

This paper cites Deep k-Nearest Neighbors: Towards Confident, Interpretable and Robust Deep Learning.

Learning Densities in Feature Space for Reliable Segmentation of Indoor Scenes Deep k-Nearest Neighbors: Towards Confident, Interpretable and Robust Deep Learning

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-14T15:59:20.470295Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation da4bacfc-5c3c-4d7c-97a5-90871f1fbf81 · outbound

This paper cites Indoor segmentation and support inference from rgbd images,.

Learning Densities in Feature Space for Reliable Segmentation of Indoor Scenes Indoor segmentation and support inference from rgbd images,

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T15:59:20.781130Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation b00cfb75-0f0a-44a6-9389-f82d5d82fa3a · outbound

This paper cites Very deep convolutional networks for large-scale image recognition,.

Learning Densities in Feature Space for Reliable Segmentation of Indoor Scenes Very deep convolutional networks for large-scale image recognition,

Reference 24

Resolution: unresolved; no resolver link, observed 2026-08-14T15:59:20.478796Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8ded341e-4df3-4f50-995e-53845bf24c87 · outbound

This paper cites Scene parsing through ade20k dataset,.

Learning Densities in Feature Space for Reliable Segmentation of Indoor Scenes Scene parsing through ade20k dataset,

Reference 25

Resolution: unresolved; no resolver link, observed 2026-08-14T15:59:20.482783Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 867eb40c-fb9b-492b-bd01-cb223111e1ea · outbound

This paper cites Distance-based Confidence Score for Neural Network Classifiers.

Learning Densities in Feature Space for Reliable Segmentation of Indoor Scenes Distance-based Confidence Score for Neural Network Classifiers

Reference 26

Resolution: unresolved; no resolver link, observed 2026-08-14T15:59:20.486620Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 79a54a55-f1d1-42ea-ac2f-3a0de6a79f61 · outbound

This paper cites The pascal visual object classes (voc) challenge,.

Learning Densities in Feature Space for Reliable Segmentation of Indoor Scenes The pascal visual object classes (voc) challenge,

Reference 27

Resolution: unresolved; no resolver link, observed 2026-08-14T15:59:20.490919Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a0518a09-bfd9-4aa6-b307-e23697429417 · outbound

This paper cites Fast k nearest neighbor search using gpu,.

Learning Densities in Feature Space for Reliable Segmentation of Indoor Scenes Fast k nearest neighbor search using gpu,

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T15:59:20.708039Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Pith citing papers

No inbound Pith citation observations are available.