Dark-ISP: Enhancing RAW Image Processing for Low-Light Object Detection | Paper Citation Record

Observation cfd090ac-5f19-43ce-a95d-5252e9d4a0d5 · outbound

This paper cites Learning generalized medical image segmentation from decoupled feature queries.

Dark-ISP: Enhancing RAW Image Processing for Low-Light Object Detection Learning generalized medical image segmentation from decoupled feature queries

Reference 1

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Observation 6e609684-09c7-4f05-96c7-992e56ed89c6 · outbound

This paper cites Unprocessing images for learned raw denoising.

Dark-ISP: Enhancing RAW Image Processing for Low-Light Object Detection Unprocessing images for learned raw denoising

Reference 2

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Observation 836d8491-fb53-4b1c-ada1-e8862abc9fde · outbound

This paper cites Cascade r-cnn: Delving into high quality object detection.

Dark-ISP: Enhancing RAW Image Processing for Low-Light Object Detection Cascade r-cnn: Delving into high quality object detection

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-04T19:37:11.929739Z

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Observation 6b9cb043-1d8f-48f5-81b1-18b78f64b744 · outbound

This paper cites Physics-guided iso-dependent sensor noise modeling for extreme low-light photography.

Dark-ISP: Enhancing RAW Image Processing for Low-Light Object Detection Physics-guided iso-dependent sensor noise modeling for extreme low-light photography

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-04T19:37:11.987164Z

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Observation 8e4aa3ab-22b9-486c-acb1-228addfec197 · outbound

This paper cites End-to- end object detection with transformers.

Dark-ISP: Enhancing RAW Image Processing for Low-Light Object Detection End-to- end object detection with transformers

Reference 5

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Observation 3c67c549-637f-485b-a0d9-11c42194bd3b · outbound

This paper cites Learning to see in the dark.

Dark-ISP: Enhancing RAW Image Processing for Low-Light Object Detection Learning to see in the dark

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-04T19:37:12.072955Z

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Observation 4115e7b7-c844-43c2-9639-5234b5e0c2d8 · outbound

This paper cites Seeing motion in the dark.

Dark-ISP: Enhancing RAW Image Processing for Low-Light Object Detection Seeing motion in the dark

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-04T19:37:12.132996Z

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Observation 29e5d665-4ebb-428e-a387-ac0aad33eaff · outbound

This paper cites Masked image training for generalizable deep image denois- ing.

Dark-ISP: Enhancing RAW Image Processing for Low-Light Object Detection Masked image training for generalizable deep image denois- ing

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-04T19:37:12.164565Z

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Observation c07efd94-966d-4aa0-b981-100474ae20e2 · outbound

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

Dark-ISP: Enhancing RAW Image Processing for Low-Light Object Detection MMDetection: Open MMLab Detection Toolbox and Benchmark

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-04T19:37:12.221965Z

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Observation 4cf9a56e-faad-4368-a730-15bef136a75a · outbound

This paper cites Instance segmentation in the dark.International Journal of Computer Vision, 131(8):2198–2218, 2023.

Dark-ISP: Enhancing RAW Image Processing for Low-Light Object Detection Instance segmentation in the dark.International Journal of Computer Vision, 131(8):2198–2218, 2023

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-04T19:37:12.310434Z

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Observation 48b4cb4e-d51d-48b6-b69c-ec54835cdee9 · outbound

This paper cites Tsdn: Two-stage raw denoising in the dark.IEEE Transactions on Image Processing, 32:3679– 3689, 2023.

Dark-ISP: Enhancing RAW Image Processing for Low-Light Object Detection Tsdn: Two-stage raw denoising in the dark.IEEE Transactions on Image Processing, 32:3679– 3689, 2023

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-04T19:37:12.397190Z

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Observation cab0e147-cc6a-4a8e-accf-8644ecd1cfe9 · outbound

This paper cites Retinex-RAWMamba: Bridging Demosaicing and Denoising for Low-Light RAW Image Enhancement.

Dark-ISP: Enhancing RAW Image Processing for Low-Light Object Detection Retinex-RAWMamba: Bridging Demosaicing and Denoising for Low-Light RAW Image Enhancement

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-04T19:37:12.428270Z

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Observation aa34a7fc-5c64-4969-bfde-5b9aca969f6b · outbound

This paper cites Nilut: Conditional neural implicit 3d lookup tables for image enhancement.

Dark-ISP: Enhancing RAW Image Processing for Low-Light Object Detection Nilut: Conditional neural implicit 3d lookup tables for image enhancement

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-04T19:37:12.485806Z

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Observation 81aae333-04ce-4848-82ec-664b81dd0e3b · outbound

This paper cites Trash to treasure: Low-light object detec- tion via decomposition-and-aggregation.

Dark-ISP: Enhancing RAW Image Processing for Low-Light Object Detection Trash to treasure: Low-light object detec- tion via decomposition-and-aggregation

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-04T19:37:12.543559Z

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Observation 3cffd7d1-757d-4016-948f-12cde980b636 · outbound

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

Dark-ISP: Enhancing RAW Image Processing for Low-Light Object Detection Raw-adapter: Adapting pre- trained visual model to camera raw images

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-04T19:37:12.570261Z

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Observation 3c5b125f-2160-4bc1-bda1-509b09d1e7e2 · outbound

This paper cites Multitask aet with orthogonal tangent regularity for dark object detection.

Dark-ISP: Enhancing RAW Image Processing for Low-Light Object Detection Multitask aet with orthogonal tangent regularity for dark object detection

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-04T19:37:12.630650Z

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Observation 4199be41-ac7a-4e13-8eaf-fffd31389086 · outbound

This paper cites DiffuseRAW: End-to-End Generative RAW Image Processing for Low-Light Images.

Dark-ISP: Enhancing RAW Image Processing for Low-Light Object Detection DiffuseRAW: End-to-End Generative RAW Image Processing for Low-Light Images

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-04T19:37:12.685895Z

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Observation 52eba4f0-6f8b-4426-9f0b-095f7a1dc377 · outbound

This paper cites Mobile computational photography: A tour.Annual review of vision science, 7(1):571–604, 2021.

Dark-ISP: Enhancing RAW Image Processing for Low-Light Object Detection Mobile computational photography: A tour.Annual review of vision science, 7(1):571–604, 2021

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-04T19:37:12.744488Z

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Observation 62ec77df-aa22-4296-948b-2215dd70f7d8 · outbound

This paper cites Dirty pixels: Towards end-to-end image processing and percep- tion.ACM Transactions on Graphics (TOG), 40(3):1–15,.

Dark-ISP: Enhancing RAW Image Processing for Low-Light Object Detection Dirty pixels: Towards end-to-end image processing and percep- tion.ACM Transactions on Graphics (TOG), 40(3):1–15,

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-04T19:37:12.772677Z

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Observation 413ab797-71d9-4d2f-a6f3-cc327f79d1ef · outbound

This paper cites Abandoning the bayer-filter to see in the dark.

Dark-ISP: Enhancing RAW Image Processing for Low-Light Object Detection Abandoning the bayer-filter to see in the dark

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-04T19:37:12.827132Z

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Observation d5afa435-9d57-403b-8234-c805856e759a · outbound

This paper cites Boosting object detection with zero-shot day-night domain adaptation.

Dark-ISP: Enhancing RAW Image Processing for Low-Light Object Detection Boosting object detection with zero-shot day-night domain adaptation

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-04T19:37:12.855141Z

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Observation 9aaf21cd-d710-44d6-a88a-0c9e2eaf8d13 · outbound

This paper cites Real- time noise-aware tone mapping.ACM Transactions on Graphics (TOG), 34(6):1–15, 2015.

Dark-ISP: Enhancing RAW Image Processing for Low-Light Object Detection Real- time noise-aware tone mapping.ACM Transactions on Graphics (TOG), 34(6):1–15, 2015

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-04T19:37:12.909027Z

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Observation 5df787d3-a90c-483c-bb58-841d76d0a49a · outbound

This paper cites Learnability enhancement for low-light raw denoising: Where paired real data meets noise modeling.

Dark-ISP: Enhancing RAW Image Processing for Low-Light Object Detection Learnability enhancement for low-light raw denoising: Where paired real data meets noise modeling

Reference 23

Resolution: unresolved; no resolver link, observed 2026-08-04T19:37:12.969541Z

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Observation 3e2e8ff8-8b4c-4191-80ed-71ccbb7f38f5 · outbound

This paper cites Fast r-cnn.

Dark-ISP: Enhancing RAW Image Processing for Low-Light Object Detection Fast r-cnn

Reference 24

Resolution: unresolved; no resolver link, observed 2026-08-04T19:37:12.998213Z

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Observation f1eacbca-6bf2-4113-906c-21a0c938069b · outbound

This paper cites Zero-reference deep curve estimation for low-light image enhancement.

Dark-ISP: Enhancing RAW Image Processing for Low-Light Object Detection Zero-reference deep curve estimation for low-light image enhancement

Reference 25

Resolution: unresolved; no resolver link, observed 2026-08-04T19:37:13.054081Z

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Observation d4b55adb-2a1d-43cd-ad9d-8c6c3172f464 · outbound

This paper cites Dynamic low-light image enhancement for object detection via end-to-end train- ing.

Dark-ISP: Enhancing RAW Image Processing for Low-Light Object Detection Dynamic low-light image enhancement for object detection via end-to-end train- ing

Reference 26

Resolution: unresolved; no resolver link, observed 2026-08-04T19:37:13.112628Z

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Observation a5a6d612-cffc-47b1-af64-cb120d463271 · outbound

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

Dark-ISP: Enhancing RAW Image Processing for Low-Light Object Detection Learn- ing degradation-independent representations for camera isp pipelines

Reference 27

Resolution: unresolved; no resolver link, observed 2026-08-04T19:37:13.166037Z

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Observation 6dbadb2b-d226-4396-bd47-a458be30ae47 · outbound

This paper cites Featenhancer: En- hancing hierarchical features for object detection and beyond under low-light vision.

Dark-ISP: Enhancing RAW Image Processing for Low-Light Object Detection Featenhancer: En- hancing hierarchical features for object detection and beyond under low-light vision

Reference 28

Resolution: unresolved; no resolver link, observed 2026-08-04T19:37:13.251823Z

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Observation 32452b3c-dac7-4c67-aaef-eb8b6b86f6cd · outbound

This paper cites Deep residual learning for image recognition.

Dark-ISP: Enhancing RAW Image Processing for Low-Light Object Detection Deep residual learning for image recognition

Reference 29

Resolution: unresolved; no resolver link, observed 2026-08-04T19:37:13.301613Z

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Observation a426fdfe-d012-4569-acf9-dab6c527eb52 · outbound

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

Dark-ISP: Enhancing RAW Image Processing for Low-Light Object Detection Craft- ing object detection in very low light

Reference 30

Resolution: unresolved; no resolver link, observed 2026-08-04T19:37:13.334476Z

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Observation 5e36fe34-94ff-4dc7-a8e2-aa1826fb90e2 · outbound

This paper cites Dnf: Decouple and feedback network for seeing in the dark.

Dark-ISP: Enhancing RAW Image Processing for Low-Light Object Detection Dnf: Decouple and feedback network for seeing in the dark

Reference 31

Resolution: unresolved; no resolver link, observed 2026-08-04T19:37:13.360426Z

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Observation c449bbf8-1b5d-42e2-860f-937588914a04 · outbound

This paper cites Lighting every darkness in two pairs: A calibration-free pipeline for raw denoising.

Dark-ISP: Enhancing RAW Image Processing for Low-Light Object Detection Lighting every darkness in two pairs: A calibration-free pipeline for raw denoising

Reference 32

Resolution: unresolved; no resolver link, observed 2026-08-04T19:37:13.419727Z

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Observation e079761d-71bf-4fbf-9888-c0a4a94a33ba · outbound

This paper cites ParamISP: Learned Forward and Inverse ISPs using Camera Parameters.

Dark-ISP: Enhancing RAW Image Processing for Low-Light Object Detection ParamISP: Learned Forward and Inverse ISPs using Camera Parameters

Reference 33

Resolution: unresolved; no resolver link, observed 2026-08-04T19:37:13.450522Z

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Observation 67d58126-4cdb-4cb7-a1d8-97e60af4d0d5 · outbound

This paper cites Local tone mapping using the k-means algorithm and automatic gamma setting.IEEE Transactions on Consumer Electron- ics, 57(1):209–217, 2011.

Dark-ISP: Enhancing RAW Image Processing for Low-Light Object Detection Local tone mapping using the k-means algorithm and automatic gamma setting.IEEE Transactions on Consumer Electron- ics, 57(1):209–217, 2011

Reference 34

Resolution: unresolved; no resolver link, observed 2026-08-04T19:37:13.504940Z

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Observation 23979e81-eafd-41a0-8091-609030baf46c · outbound

This paper cites Dualdn: Dual-domain denoising via differ- entiable isp.

Dark-ISP: Enhancing RAW Image Processing for Low-Light Object Detection Dualdn: Dual-domain denoising via differ- entiable isp

Reference 35

Resolution: unresolved; no resolver link, observed 2026-08-04T19:37:13.589559Z

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Observation 8ce76ebf-d6ad-4eb7-a46e-5500ab6f1cfb · outbound

This paper cites A dark transformation-equivariant al- gorithm for dark object detection.

Dark-ISP: Enhancing RAW Image Processing for Low-Light Object Detection A dark transformation-equivariant al- gorithm for dark object detection

Reference 36

Resolution: unresolved; no resolver link, observed 2026-08-04T19:37:13.641799Z

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Observation d32cad8c-90fe-4fbf-ad3d-04920991f994 · outbound

This paper cites Microsoft coco: Common objects in context.

Dark-ISP: Enhancing RAW Image Processing for Low-Light Object Detection Microsoft coco: Common objects in context

Reference 37

Resolution: unresolved; no resolver link, observed 2026-08-04T19:37:13.675756Z

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Observation 1f2d914a-f204-4b51-9de8-f812078422a3 · outbound

This paper cites Focal loss for dense object detection.

Dark-ISP: Enhancing RAW Image Processing for Low-Light Object Detection Focal loss for dense object detection

Reference 38

Resolution: unresolved; no resolver link, observed 2026-08-04T19:37:13.698801Z

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Observation 682f9cc8-d9d0-4348-94c7-66b30705d499 · outbound

This paper cites Un- supervised image denoising in real-world scenarios via self- collaboration parallel generative adversarial branches.

Dark-ISP: Enhancing RAW Image Processing for Low-Light Object Detection Un- supervised image denoising in real-world scenarios via self- collaboration parallel generative adversarial branches

Reference 39

Resolution: unresolved; no resolver link, observed 2026-08-04T19:37:13.758530Z

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Observation 2f77b3b4-b362-4ef4-ba0f-69ceb3b94b0a · outbound

This paper cites Raw or cooked? object detection on raw images.

Dark-ISP: Enhancing RAW Image Processing for Low-Light Object Detection Raw or cooked? object detection on raw images

Reference 40

Resolution: unresolved; no resolver link, observed 2026-08-04T19:37:13.818086Z

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Observation 2b70d829-88ea-46b2-af9a-a6ffa00e8a3d · outbound

This paper cites Genisp: Neural isp for low-light machine cognition.

Dark-ISP: Enhancing RAW Image Processing for Low-Light Object Detection Genisp: Neural isp for low-light machine cognition

Reference 41

Resolution: unresolved; no resolver link, observed 2026-08-04T19:37:13.850574Z

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Observation bbeeda1c-0f3b-4e46-bd4c-ff482d64537b · outbound

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

Dark-ISP: Enhancing RAW Image Processing for Low-Light Object Detection Hardware-in- the-loop end-to-end optimization of camera image process- ing pipelines

Reference 42

Resolution: unresolved; no resolver link, observed 2026-08-04T19:37:13.904644Z

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Observation 1da3b56f-257c-490a-a527-5b6624507b09 · outbound

This paper cites A novel low light object detection method based on the yolov5 fusion feature enhancement.Scientific reports, 14(1):4486, 2024.

Dark-ISP: Enhancing RAW Image Processing for Low-Light Object Detection A novel low light object detection method based on the yolov5 fusion feature enhancement.Scientific reports, 14(1):4486, 2024

Reference 43

Resolution: unresolved; no resolver link, observed 2026-08-04T19:37:13.934236Z

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Observation f49f1fc4-2ff1-4ca1-a36f-303a16a93596 · outbound

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

Dark-ISP: Enhancing RAW Image Processing for Low-Light Object Detection Attention-aware learning for hyperparameter prediction in image processing pipelines

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Resolution: unresolved; no resolver link, observed 2026-08-04T19:37:14.020731Z

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Observation a9ceb816-4eb0-48e7-9385-473a306d7be4 · outbound

This paper cites You only look once: Unified, real-time object de- tection.

Dark-ISP: Enhancing RAW Image Processing for Low-Light Object Detection You only look once: Unified, real-time object de- tection

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Resolution: unresolved; no resolver link, observed 2026-08-04T19:37:14.074560Z

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Observation ab02869d-e95a-422d-8a87-0fcfc0238e3f · outbound

This paper cites Embeddedpigdet—fast and accurate pig detection for embedded board implementations.

Dark-ISP: Enhancing RAW Image Processing for Low-Light Object Detection Embeddedpigdet—fast and accurate pig detection for embedded board implementations

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Resolution: unresolved; no resolver link, observed 2026-08-04T19:37:14.132548Z

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Observation 17f12500-cd85-4644-abb1-d98af084a800 · outbound

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

Dark-ISP: Enhancing RAW Image Processing for Low-Light Object Detection Sparse r-cnn: End-to-end ob- ject detection with learnable proposals

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Resolution: unresolved; no resolver link, observed 2026-08-04T19:37:14.190180Z

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Observation eb982463-2e96-4353-bd7e-efb50e3c9a9a · outbound

This paper cites Attention is all you need.Advances in neural information processing systems, 30, 2017.

Dark-ISP: Enhancing RAW Image Processing for Low-Light Object Detection Attention is all you need.Advances in neural information processing systems, 30, 2017

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Resolution: unresolved; no resolver link, observed 2026-08-04T19:37:14.219072Z

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Observation ad25d899-741a-44a7-bcdc-976b228636aa · outbound

This paper cites Real-time image en- hancer via learnable spatial-aware 3d lookup tables.

Dark-ISP: Enhancing RAW Image Processing for Low-Light Object Detection Real-time image en- hancer via learnable spatial-aware 3d lookup tables

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Resolution: unresolved; no resolver link, observed 2026-08-04T19:37:14.275211Z

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Observation b176c99e-9855-49f2-b08a-85c420f2401d · outbound

This paper cites Exposurediffusion: Learning to expose for low-light image enhancement.

Dark-ISP: Enhancing RAW Image Processing for Low-Light Object Detection Exposurediffusion: Learning to expose for low-light image enhancement

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Resolution: unresolved; no resolver link, observed 2026-08-04T19:37:14.332517Z

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Observation dbb93056-7b49-4962-9246-0d22be15c989 · outbound

This paper cites Adaptiveisp: Learning an adaptive image signal pro- cessor for object detection.Advances in Neural Information Processing Systems, 37:112598–112623, 2024.

Dark-ISP: Enhancing RAW Image Processing for Low-Light Object Detection Adaptiveisp: Learning an adaptive image signal pro- cessor for object detection.Advances in Neural Information Processing Systems, 37:112598–112623, 2024

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Resolution: unresolved; no resolver link, observed 2026-08-04T19:37:14.414825Z

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Observation c29f15d5-6914-4507-9b9e-0cced05f7ce6 · outbound

This paper cites Adaptiveisp: Learning an adaptive image signal pro- cessor for object detection.Advances in Neural Information Processing Systems, 37:112598–112623, 2025.

Dark-ISP: Enhancing RAW Image Processing for Low-Light Object Detection Adaptiveisp: Learning an adaptive image signal pro- cessor for object detection.Advances in Neural Information Processing Systems, 37:112598–112623, 2025

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Resolution: unresolved; no resolver link, observed 2026-08-04T19:37:14.473835Z

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Observation a57c21e7-2286-4883-aa12-60760c98a080 · outbound

This paper cites A physics-based noise formation model for extreme low-light raw denoising.

Dark-ISP: Enhancing RAW Image Processing for Low-Light Object Detection A physics-based noise formation model for extreme low-light raw denoising

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Resolution: unresolved; no resolver link, observed 2026-08-04T19:37:14.502612Z

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Observation 172a131f-1b64-4ddc-a330-c86f0e2639bd · outbound

This paper cites Physics-based noise modeling for extreme low-light photog- raphy.IEEE Transactions on Pattern Analysis and Machine Intelligence, page 1–1, 2021.

Dark-ISP: Enhancing RAW Image Processing for Low-Light Object Detection Physics-based noise modeling for extreme low-light photog- raphy.IEEE Transactions on Pattern Analysis and Machine Intelligence, page 1–1, 2021

Reference 54

Resolution: unresolved; no resolver link, observed 2026-08-04T19:37:14.527892Z

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Observation 4ee288e4-a277-490c-b0ce-bf5397f51587 · outbound

This paper cites Invertible im- age signal processing.

Dark-ISP: Enhancing RAW Image Processing for Low-Light Object Detection Invertible im- age signal processing

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Resolution: unresolved; no resolver link, observed 2026-08-04T19:37:14.586485Z

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Observation a889129d-e145-4e1b-895b-6acd40d7709e · outbound

This paper cites Rawformer: An efficient vision transformer for low-light raw image enhancement.IEEE Signal Process- ing Letters, 29:2677–2681, 2022.

Dark-ISP: Enhancing RAW Image Processing for Low-Light Object Detection Rawformer: An efficient vision transformer for low-light raw image enhancement.IEEE Signal Process- ing Letters, 29:2677–2681, 2022

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Resolution: unresolved; no resolver link, observed 2026-08-04T19:37:14.644033Z

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Observation ffcb2a6e-5dbc-4096-a1d9-6144ca55900e · outbound

This paper cites Exploring image enhancement for salient object detection in low light images.ACM transactions on multime- dia computing, communications, and applications (TOMM), 17(1s):1–19, 2021.

Dark-ISP: Enhancing RAW Image Processing for Low-Light Object Detection Exploring image enhancement for salient object detection in low light images.ACM transactions on multime- dia computing, communications, and applications (TOMM), 17(1s):1–19, 2021

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Observation 255994f8-1a5a-4df3-97e7-37a8211df01b · outbound

This paper cites Best of both worlds: See and understand clearly in the dark.

Dark-ISP: Enhancing RAW Image Processing for Low-Light Object Detection Best of both worlds: See and understand clearly in the dark

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Observation 7528a89d-2630-4c65-a79b-0c4e7395a5c5 · outbound

This paper cites Seplut: Separable image-adaptive lookup tables for real-time image enhancement.

Dark-ISP: Enhancing RAW Image Processing for Low-Light Object Detection Seplut: Separable image-adaptive lookup tables for real-time image enhancement

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Observation 52c4d783-adc3-434d-9545-5ace2097bcd1 · outbound

This paper cites Dynamicisp: dynamically controlled image signal processor for image recognition.

Dark-ISP: Enhancing RAW Image Processing for Low-Light Object Detection Dynamicisp: dynamically controlled image signal processor for image recognition

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Observation adb8ffce-ddb3-4a2b-ac56-20c3bdabbafb · outbound

This paper cites Cycleisp: Real image restoration via improved data synthesis.

Dark-ISP: Enhancing RAW Image Processing for Low-Light Object Detection Cycleisp: Real image restoration via improved data synthesis

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Observation 7f65d3a8-75cc-4b4e-b7c7-b2f38074927c · outbound

This paper cites Learning image-adaptive 3d lookup tables for high perfor- mance photo enhancement in real-time.IEEE Transactions on Pattern Analysis and Machine Intelligence, 44(4), 2020.

Dark-ISP: Enhancing RAW Image Processing for Low-Light Object Detection Learning image-adaptive 3d lookup tables for high perfor- mance photo enhancement in real-time.IEEE Transactions on Pattern Analysis and Machine Intelligence, 44(4), 2020

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Resolution: unresolved; no resolver link, observed 2026-08-04T19:37:14.899798Z

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Observation 11ddea9d-d011-4d17-8638-72117470f235 · outbound

This paper cites Towards general low- light raw noise synthesis and modeling.

Dark-ISP: Enhancing RAW Image Processing for Low-Light Object Detection Towards general low- light raw noise synthesis and modeling

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Observation 7ca1f8c2-f273-47d2-8a2f-a107c84db35a · outbound

This paper cites Featurized Query R-CNN.

Dark-ISP: Enhancing RAW Image Processing for Low-Light Object Detection Featurized Query R-CNN

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Observation d1315371-bcec-4e5d-8fbd-8076d80b7444 · outbound

This paper cites Rethinking noise synthesis and modeling in raw denois- ing.

Dark-ISP: Enhancing RAW Image Processing for Low-Light Object Detection Rethinking noise synthesis and modeling in raw denois- ing

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Observation 03451618-0413-4b3d-ae1a-2f4c00f653ff · outbound

This paper cites Isp-teacher: image signal pro- cess with disentanglement regularization for unsupervised domain adaptive dark object detection.

Dark-ISP: Enhancing RAW Image Processing for Low-Light Object Detection Isp-teacher: image signal pro- cess with disentanglement regularization for unsupervised domain adaptive dark object detection

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Resolution: unresolved; no resolver link, observed 2026-08-04T19:37:15.202972Z

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Observation 3622a01e-132d-47ca-96d4-985e2e8aa404 · outbound

This paper cites Restoration for weakly blurred and strongly noisy images.

Dark-ISP: Enhancing RAW Image Processing for Low-Light Object Detection Restoration for weakly blurred and strongly noisy images

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Observation f0b8ed30-de49-4c78-abec-3514e6441db4 · outbound

This paper cites Deformable detr: Deformable transform- ers for end-to-end object detection.arXiv: Computer Vision and Pattern Recognition,arXiv: Computer Vision and Pat- tern Recognition, 2020.

Dark-ISP: Enhancing RAW Image Processing for Low-Light Object Detection Deformable detr: Deformable transform- ers for end-to-end object detection.arXiv: Computer Vision and Pattern Recognition,arXiv: Computer Vision and Pat- tern Recognition, 2020

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