Paper Citation Record · LEDGER

Towards RAW Object Detection in Diverse Conditions

As of 22 August 2026, this Paper Citation Record lists 42 of 42 outbound references and 2 inbound Pith citation observations for arXiv:2411.15678.

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

pith.paper-citation-record.v1
2411.15678 v1

Coverage vector

measured 42 of 42 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-12T14:05:09.127528Z

measured 44 of 44 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-21T06:32:19.484+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-06T20:52:02.511743Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-06T15:03:17.060212Z

Reference resolution

42 of 42 outbound references displayed

verified exact0
verified fuzzy32
unresolved10
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation fe9f9faf-e372-4d90-aef8-1619a65067f2 · outbound

This paper cites Seeing through fog without seeing fog: Deep multimodal sensor fu- sion in unseen adverse weather.

Towards RAW Object Detection in Diverse Conditions Seeing through fog without seeing fog: Deep multimodal sensor fu- sion in unseen adverse weather

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T14:05:09.760184Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 8b47cdcb-1d11-4bb0-b32a-f32bc091d645 · outbound

This paper cites Unprocessing im- ages for learned raw denoising.

Towards RAW Object Detection in Diverse Conditions Unprocessing im- ages for learned raw denoising

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T14:05:09.744582Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 4ba167e5-31fc-46e9-b62e-bf23c3909ef8 · outbound

This paper cites Cascade r-cnn: High quality object detection and instance segmentation.

Towards RAW Object Detection in Diverse Conditions Cascade r-cnn: High quality object detection and instance segmentation

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T14:05:09.730468Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 862f8ee9-1e58-44d0-bbdd-ef57328b8430 · outbound

This paper cites MMDetection: Open MMLab Detection Toolbox and Benchmark.

Towards RAW Object Detection in Diverse Conditions MMDetection: Open MMLab Detection Toolbox and Benchmark

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-12T14:05:08.963107Z

Source-reported events for the cited work

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Observation c7177172-9128-4090-967e-d30109457932 · outbound

This paper cites Instance segmentation in the dark.

Towards RAW Object Detection in Diverse Conditions Instance segmentation in the dark

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T14:05:09.716091Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation ee592921-8e86-475f-9efd-c420b120cdc0 · outbound

This paper cites YOLO-MS: Rethinking Multi-Scale Representation Learning for Real-time Object Detection.

Towards RAW Object Detection in Diverse Conditions YOLO-MS: Rethinking Multi-Scale Representation Learning for Real-time Object Detection

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-12T14:05:08.971807Z

Source-reported events for the cited work

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Observation d7008d22-1498-4aa3-9266-247ab66ffd24 · outbound

This paper cites Towards large-scale small object detection: Survey and benchmarks.

Towards RAW Object Detection in Diverse Conditions Towards large-scale small object detection: Survey and benchmarks

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T14:05:09.700486Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 7cfa9196-29a2-44b9-8e85-b084831db91c · outbound

This paper cites Raw-adapter: Adapting pre- trained visual model to camera raw images.

Towards RAW Object Detection in Diverse Conditions Raw-adapter: Adapting pre- trained visual model to camera raw images

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T14:05:09.681919Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 503500c3-5c8e-46c6-98cb-107fb50a46f7 · outbound

This paper cites Dirty pixels: Towards end-to-end image processing and percep- tion.

Towards RAW Object Detection in Diverse Conditions Dirty pixels: Towards end-to-end image processing and percep- tion

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T14:05:09.665954Z

Source-reported events for the cited work

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Observation 0dcb8a27-bc82-4295-933c-d3661e03eb33 · outbound

This paper cites Everingham, L.

Towards RAW Object Detection in Diverse Conditions Everingham, L

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T14:05:09.650009Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 3d8c7e44-e8a7-4bbe-88f6-13c7e3da542f · outbound

This paper cites YOLOX: Exceeding YOLO Series in 2021.

Towards RAW Object Detection in Diverse Conditions YOLOX: Exceeding YOLO Series in 2021

Reference 11

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Source-reported events for the cited work

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Observation 9faa3418-ea8e-4d72-a016-bce8dc26122f · outbound

This paper cites Gamma cor- rection for digital fringe projection profilometry.

Towards RAW Object Detection in Diverse Conditions Gamma cor- rection for digital fringe projection profilometry

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T14:05:09.635560Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 80fd4dd8-954d-405d-839d-73fcec6b4bb8 · outbound

This paper cites Learn- ing degradation-independent representations for camera isp pipelines.

Towards RAW Object Detection in Diverse Conditions Learn- ing degradation-independent representations for camera isp pipelines

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T14:05:09.621210Z

Source-reported events for the cited work

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Observation d19555ba-57d8-40b4-b989-b9fecd1477f4 · outbound

This paper cites Deep residual learning for image recognition.

Towards RAW Object Detection in Diverse Conditions Deep residual learning for image recognition

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-12T14:05:09.007694Z

Source-reported events for the cited work

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Observation 44cd0f9d-4f8b-4b05-8ba7-28afbf8219b5 · outbound

This paper cites Masked autoencoders are scalable vision learners.

Towards RAW Object Detection in Diverse Conditions Masked autoencoders are scalable vision learners

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T14:05:09.595629Z

Source-reported events for the cited work

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Observation 918953df-a880-431a-b184-3d9b52a60a00 · outbound

This paper cites Distilling the Knowledge in a Neural Network.

Towards RAW Object Detection in Diverse Conditions Distilling the Knowledge in a Neural Network

Reference 16

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Source-reported events for the cited work

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Observation 2a6a313f-bd6d-4cfa-9436-59562b273caa · outbound

This paper cites Craft- ing object detection in very low light.

Towards RAW Object Detection in Diverse Conditions Craft- ing object detection in very low light

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T14:05:09.579438Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 9106bd64-cc7f-4ef6-b83a-7a01ebb8a7f6 · outbound

This paper cites YOLO by Ultralytics, 2023.

Towards RAW Object Detection in Diverse Conditions YOLO by Ultralytics, 2023

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T14:05:09.564341Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation e0b06e64-b22e-4e87-a676-feaaec7b16bf · outbound

This paper cites Generalized focal loss: Learning qualified and distributed bounding boxes for dense object detection.

Towards RAW Object Detection in Diverse Conditions Generalized focal loss: Learning qualified and distributed bounding boxes for dense object detection

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T14:05:09.550579Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation e1df4845-b295-4e03-a2d8-5b2e68ce135e · outbound

This paper cites Salman Asif, and Zhan Ma.

Towards RAW Object Detection in Diverse Conditions Salman Asif, and Zhan Ma

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T14:05:09.536951Z

Source-reported events for the cited work

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Observation 2715d1be-ae96-41a8-b656-c8ae6c29eff5 · outbound

This paper cites Microsoft coco: Common objects in context.

Towards RAW Object Detection in Diverse Conditions Microsoft coco: Common objects in context

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T14:05:09.521798Z

Source-reported events for the cited work

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Observation a236ba32-f2a0-4a69-ae9c-70d0cd1a8859 · outbound

This paper cites Focal loss for dense object detection.

Towards RAW Object Detection in Diverse Conditions Focal loss for dense object detection

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-12T14:05:09.042916Z

Source-reported events for the cited work

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Observation d2dbc68c-d8c3-4090-9767-f3b7e0b8fe97 · outbound

This paper cites Swin transformer: Hierarchical vision transformer using shifted windows.

Towards RAW Object Detection in Diverse Conditions Swin transformer: Hierarchical vision transformer using shifted windows

Reference 23

Resolution: unresolved; no resolver link, observed 2026-08-12T14:05:09.047328Z

Source-reported events for the cited work

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Observation a3346959-a25a-44ae-9bd1-6f29ac74e79b · outbound

This paper cites A convnet for the 2020s.

Towards RAW Object Detection in Diverse Conditions A convnet for the 2020s

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T14:05:09.488816Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 4704cd45-6397-4ba1-b162-35da56d5684c · outbound

This paper cites Hardware-in- the-loop end-to-end optimization of camera image process- ing pipelines.

Towards RAW Object Detection in Diverse Conditions Hardware-in- the-loop end-to-end optimization of camera image process- ing pipelines

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T14:05:09.475489Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 4d785f6f-f559-4e47-b0d5-5e2239bcfbbd · outbound

This paper cites Pas- calraw: raw image database for object detection.

Towards RAW Object Detection in Diverse Conditions Pas- calraw: raw image database for object detection

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T14:05:09.461646Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 049b2b2b-5c04-4e28-ad15-73b51bd6037e · outbound

This paper cites Attention-aware learning for hyperparameter prediction in image processing pipelines.

Towards RAW Object Detection in Diverse Conditions Attention-aware learning for hyperparameter prediction in image processing pipelines

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T14:05:09.448286Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 30ffaf35-e66e-41eb-9d32-5caef4beead6 · outbound

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

Towards RAW Object Detection in Diverse Conditions Faster r-cnn: Towards real-time object detection with region proposal networks

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T14:05:09.433842Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 448e2873-b71e-423c-8fd8-14b8797c4b98 · outbound

This paper cites Imagenet large scale visual recognition challenge.

Towards RAW Object Detection in Diverse Conditions Imagenet large scale visual recognition challenge

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T14:05:09.419338Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation e57f0991-8cc2-4026-94cc-de03b37eb1a3 · outbound

This paper cites Sparse r-cnn: End-to-end object detection with learnable proposals.

Towards RAW Object Detection in Diverse Conditions Sparse r-cnn: End-to-end object detection with learnable proposals

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T14:05:09.405220Z

Source-reported events for the cited work

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Observation ecfc20cc-9eaf-4be2-9ae1-3b9be2c3b697 · outbound

This paper cites Adaptiveisp: Learning an adaptive image signal proces- sor for object detection.

Towards RAW Object Detection in Diverse Conditions Adaptiveisp: Learning an adaptive image signal proces- sor for object detection

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T14:05:09.391385Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation a3018290-cca3-49e7-9448-6e65151ba87e · outbound

This paper cites Contrastive Learning Rivals Masked Image Modeling in Fine-tuning via Feature Distillation.

Towards RAW Object Detection in Diverse Conditions Contrastive Learning Rivals Masked Image Modeling in Fine-tuning via Feature Distillation

Reference 32

Resolution: unresolved; no resolver link, observed 2026-08-12T14:05:09.083606Z

Source-reported events for the cited work

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Observation 411e5017-f30c-49cc-b63a-e8e9bcf1d46d · outbound

This paper cites Isikdogan, Sushma Rao, Bhavin Nayak, Timo Gerasimow, Aleksandar Sutic, Liron Ain- kedem, and Gilad Michael.

Towards RAW Object Detection in Diverse Conditions Isikdogan, Sushma Rao, Bhavin Nayak, Timo Gerasimow, Aleksandar Sutic, Liron Ain- kedem, and Gilad Michael

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T14:05:09.377044Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation a0768b82-0562-4c68-bfcd-e9eac33e5645 · outbound

This paper cites Toward raw object detection: A new benchmark and a new model.

Towards RAW Object Detection in Diverse Conditions Toward raw object detection: A new benchmark and a new model

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T14:05:09.362665Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 64cff233-a3df-44cf-b752-74e5fe5202b5 · outbound

This paper cites Dynamicisp: Dynamically controlled im- age signal processor for image recognition.

Towards RAW Object Detection in Diverse Conditions Dynamicisp: Dynamically controlled im- age signal processor for image recognition

Reference 35

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T14:05:09.348375Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation f864112d-606e-4d19-9050-75d3823afbb2 · outbound

This paper cites Reconfigisp: Reconfigurable camera image processing pipeline.

Towards RAW Object Detection in Diverse Conditions Reconfigisp: Reconfigurable camera image processing pipeline

Reference 36

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T14:05:09.333699Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 6acc4e6e-653a-4c9c-9ffa-d77f3e4a4941 · outbound

This paper cites DarkVision: A Benchmark for Low-light Image/Video Perception.

Towards RAW Object Detection in Diverse Conditions DarkVision: A Benchmark for Low-light Image/Video Perception

Reference 37

Resolution: unresolved; no resolver link, observed 2026-08-12T14:05:09.104645Z

Source-reported events for the cited work

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Observation a55aed54-0690-40c4-9d0b-e0fa620f6339 · outbound

This paper cites Deformable detr: Deformable transformers for end-to-end object detection.

Towards RAW Object Detection in Diverse Conditions Deformable detr: Deformable transformers for end-to-end object detection

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T14:05:09.318887Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 6d06db4a-0ef0-4f17-b70c-e4b9ecf20ce3 · outbound

This paper cites We collect images under 9 conditions, as shown in Tab.

Towards RAW Object Detection in Diverse Conditions We collect images under 9 conditions, as shown in Tab

Reference 39

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T14:05:09.303645Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 6e2e8f57-1c4a-4201-9f43-838775099ecb · outbound

This paper cites For data augmentations, the images are re- sized between 800 and 1024 along the shorter side, while the longer side is no larger than 2048.

Towards RAW Object Detection in Diverse Conditions For data augmentations, the images are re- sized between 800 and 1024 along the shorter side, while the longer side is no larger than 2048

Reference 41

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T14:05:09.274669Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation ecc95828-bc60-43dc-a432-846d854b6337 · outbound

This paper cites Besides the supervised classification loss func- tion, we use logit-based and feature-based distillation for cross-domain distillation.

Towards RAW Object Detection in Diverse Conditions Besides the supervised classification loss func- tion, we use logit-based and feature-based distillation for cross-domain distillation

Reference 42

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T14:05:09.259432Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation f0746c25-62db-478e-9a42-35d55fe3bc24 · outbound

This paper cites an unresolved cited work.

Towards RAW Object Detection in Diverse Conditions Unresolved cited work

Reference 100

Resolution: unresolved; raw_fallback, observed 2026-08-12T14:05:09.288993Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Pith citing papers

Observation 5f98272d-3d24-413d-8a74-060de963d6b3 · inbound

Depth Anything at Any Condition cites this paper.

Depth Anything at Any Condition Towards RAW Object Detection in Diverse Conditions

Reference 45

Resolution: unresolved; no resolver link, observed 2026-08-06T20:52:02.511743Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 489a5701-7f64-4c9f-819b-2e61632c9790 · inbound

UNICE: Training A Universal Image Contrast Enhancer cites this paper.

UNICE: Training A Universal Image Contrast Enhancer Towards RAW Object Detection in Diverse Conditions

Reference 45

Resolution: verified exact; local_arxiv, observed 2026-08-06T15:03:17.150345Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.