Unveiling the Underwater World: CLIP Perception Model-Guided Underwater Image Enhancement | Paper Citation Record

Observation e6c0cc91-606d-4116-a6a8-2d82ca0852d0 · outbound

This paper cites Uncertainty inspired underwater image enhancement,.

Unveiling the Underwater World: CLIP Perception Model-Guided Underwater Image Enhancement Uncertainty inspired underwater image enhancement,

Reference 1

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Observation b9899832-e001-4ae5-9a16-a7a88613a27b · outbound

This paper cites An in-depth survey of underwater image enhancement and restoration,.

Unveiling the Underwater World: CLIP Perception Model-Guided Underwater Image Enhancement An in-depth survey of underwater image enhancement and restoration,

Reference 2

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Observation b22242f9-8584-48ae-a57e-9f8d95461e92 · outbound

This paper cites A survey on underwater image en- hancement techniques,.

Unveiling the Underwater World: CLIP Perception Model-Guided Underwater Image Enhancement A survey on underwater image en- hancement techniques,

Reference 3

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This paper cites an unresolved cited work.

Unveiling the Underwater World: CLIP Perception Model-Guided Underwater Image Enhancement Unresolved cited work

Reference 4

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This paper cites The marine strategy framework directive: a new european approach to the regulation of the marine environment, marine natural resources and marine ecological services,.

Unveiling the Underwater World: CLIP Perception Model-Guided Underwater Image Enhancement The marine strategy framework directive: a new european approach to the regulation of the marine environment, marine natural resources and marine ecological services,

Reference 5

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Observation f49bc51b-c17d-4953-9c9a-5fa4d53be47a · outbound

This paper cites Towards an urban marine ecology: characterizing the drivers, patterns and processes of marine ecosystems in coastal cities,.

Unveiling the Underwater World: CLIP Perception Model-Guided Underwater Image Enhancement Towards an urban marine ecology: characterizing the drivers, patterns and processes of marine ecosystems in coastal cities,

Reference 6

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Observation 69b81118-dd13-44b3-a8e9-8d08db77cf0e · outbound

This paper cites Underwater image processing: state of the art of restoration and image enhancement methods,.

Unveiling the Underwater World: CLIP Perception Model-Guided Underwater Image Enhancement Underwater image processing: state of the art of restoration and image enhancement methods,

Reference 7

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Observation 8bf6ff64-dbb3-4b01-8662-17438ac1a7f7 · outbound

This paper cites Enhancing underwa- ter images and videos by fusion,.

Unveiling the Underwater World: CLIP Perception Model-Guided Underwater Image Enhancement Enhancing underwa- ter images and videos by fusion,

Reference 8

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Observation 736cab30-1156-4422-8ceb-6dd91fe5800d · outbound

This paper cites Enhancing the low quality images using unsupervised colour correction method,.

Unveiling the Underwater World: CLIP Perception Model-Guided Underwater Image Enhancement Enhancing the low quality images using unsupervised colour correction method,

Reference 9

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Observation 09d4c84d-5d6a-45c1-b2a3-d719f7a7e408 · outbound

This paper cites Single image haze removal using dark channel prior,.

Unveiling the Underwater World: CLIP Perception Model-Guided Underwater Image Enhancement Single image haze removal using dark channel prior,

Reference 10

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Observation 4fdc0b65-eb19-44f9-8928-708dbe020212 · outbound

This paper cites Underwater depth estimation and image restoration based on single images,.

Unveiling the Underwater World: CLIP Perception Model-Guided Underwater Image Enhancement Underwater depth estimation and image restoration based on single images,

Reference 11

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Observation 21dc37cc-ca3a-4fb1-a80a-be77271ef09d · outbound

This paper cites Underwater image enhancement by dehazing with minimum information loss and histogram distribution prior,.

Unveiling the Underwater World: CLIP Perception Model-Guided Underwater Image Enhancement Underwater image enhancement by dehazing with minimum information loss and histogram distribution prior,

Reference 12

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Observation 2313f2f5-bfae-40e8-994c-e04a10e7dbe8 · outbound

This paper cites Object detection in 20 years: A survey,.

Unveiling the Underwater World: CLIP Perception Model-Guided Underwater Image Enhancement Object detection in 20 years: A survey,

Reference 13

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Observation 0f14b4af-1641-4cc7-9bbd-025588861b4a · outbound

This paper cites Underwater image enhancement using a multiscale dense generative adversarial network,.

Unveiling the Underwater World: CLIP Perception Model-Guided Underwater Image Enhancement Underwater image enhancement using a multiscale dense generative adversarial network,

Reference 14

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Observation 25462463-0c7a-42cf-aa06-8ccaa502aab0 · outbound

This paper cites Water- GAN: Unsupervised generative network to enable real-time color correc- tion of monocular underwater images,.

Unveiling the Underwater World: CLIP Perception Model-Guided Underwater Image Enhancement Water- GAN: Unsupervised generative network to enable real-time color correc- tion of monocular underwater images,

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T05:35:23.004093Z

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Observation 72c10513-e227-4dea-b0de-ff43d19d6ae3 · outbound

This paper cites Underwater image enhancement via medium transmission-guided multi-color space embedding,.

Unveiling the Underwater World: CLIP Perception Model-Guided Underwater Image Enhancement Underwater image enhancement via medium transmission-guided multi-color space embedding,

Reference 16

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Observation e607e064-1fa1-4a8a-a42e-1a075aa8db94 · outbound

This paper cites Sea-thru: A method for removing water from underwater images,.

Unveiling the Underwater World: CLIP Perception Model-Guided Underwater Image Enhancement Sea-thru: A method for removing water from underwater images,

Reference 17

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Observation 11d5fa34-3b70-45eb-acec-6fc1cfaae82a · outbound

This paper cites An underwater image enhancement benchmark dataset and beyond,.

Unveiling the Underwater World: CLIP Perception Model-Guided Underwater Image Enhancement An underwater image enhancement benchmark dataset and beyond,

Reference 18

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Observation 30734b8e-ebe5-47e3-ae96-d185dd82b521 · outbound

This paper cites U-shape transformer for underwater image enhancement,.

Unveiling the Underwater World: CLIP Perception Model-Guided Underwater Image Enhancement U-shape transformer for underwater image enhancement,

Reference 19

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Observation 42a6c0ac-408c-4203-a795-966d14295b89 · outbound

This paper cites Underwater ranker: Learn which is better and how to be better,.

Unveiling the Underwater World: CLIP Perception Model-Guided Underwater Image Enhancement Underwater ranker: Learn which is better and how to be better,

Reference 20

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Observation 7b9957b8-931a-44d5-9e93-79854eb63379 · outbound

This paper cites Exploring clip for assessing the look and feel of images,.

Unveiling the Underwater World: CLIP Perception Model-Guided Underwater Image Enhancement Exploring clip for assessing the look and feel of images,

Reference 21

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Observation a78424b1-a5b3-4e55-bd65-9e97f43a10a7 · outbound

This paper cites Curricular contrastive regularization for physics-aware single image dehazing,.

Unveiling the Underwater World: CLIP Perception Model-Guided Underwater Image Enhancement Curricular contrastive regularization for physics-aware single image dehazing,

Reference 22

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Observation 448677ef-0351-4617-abff-55970ecab84a · outbound

This paper cites Learning transferable visual models from natural language supervision,.

Unveiling the Underwater World: CLIP Perception Model-Guided Underwater Image Enhancement Learning transferable visual models from natural language supervision,

Reference 23

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Observation a53a8da3-95fd-4bb1-896b-132f6f221ef2 · outbound

This paper cites Contrastive learning for compact single image dehazing,.

Unveiling the Underwater World: CLIP Perception Model-Guided Underwater Image Enhancement Contrastive learning for compact single image dehazing,

Reference 24

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Observation f63d7303-431e-4e03-9da3-b3f9ec0f51a4 · outbound

This paper cites Generalization of the dark channel prior for single image restoration,.

Unveiling the Underwater World: CLIP Perception Model-Guided Underwater Image Enhancement Generalization of the dark channel prior for single image restoration,

Reference 25

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This paper cites Automatic red- channel underwater image restoration,.

Unveiling the Underwater World: CLIP Perception Model-Guided Underwater Image Enhancement Automatic red- channel underwater image restoration,

Reference 26

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Observation 55711fc4-13d9-4a57-8040-1c6b258c952f · outbound

This paper cites Underwater image restoration based on image blurriness and light absorption,.

Unveiling the Underwater World: CLIP Perception Model-Guided Underwater Image Enhancement Underwater image restoration based on image blurriness and light absorption,

Reference 27

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Observation 61db8672-a24d-4e44-8799-2f18fe84463f · outbound

This paper cites Shallow-uwnet: Compressed model for underwater image enhancement (student abstract),.

Unveiling the Underwater World: CLIP Perception Model-Guided Underwater Image Enhancement Shallow-uwnet: Compressed model for underwater image enhancement (student abstract),

Reference 28

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Observation c140082f-270f-4711-8553-fdd64d578b37 · outbound

This paper cites UIECˆ 2-Net: Cnn-based under- water image enhancement using two color space,.

Unveiling the Underwater World: CLIP Perception Model-Guided Underwater Image Enhancement UIECˆ 2-Net: Cnn-based under- water image enhancement using two color space,

Reference 29

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Observation 5b103661-4a4e-4307-8cba-20fcdae333b6 · outbound

This paper cites Uncertainty inspired underwater image enhancement,.

Unveiling the Underwater World: CLIP Perception Model-Guided Underwater Image Enhancement Uncertainty inspired underwater image enhancement,

Reference 30

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Observation fa60e43b-62c5-4613-85f3-98a8bac2c6ab · outbound

This paper cites Enhancing underwater imagery using generative adversarial networks,.

Unveiling the Underwater World: CLIP Perception Model-Guided Underwater Image Enhancement Enhancing underwater imagery using generative adversarial networks,

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T05:35:22.815051Z

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Observation 17bbe1c8-367f-400c-85fe-fa5c5e5143ec · outbound

This paper cites Open-vocabulary detr with conditional matching,.

Unveiling the Underwater World: CLIP Perception Model-Guided Underwater Image Enhancement Open-vocabulary detr with conditional matching,

Reference 32

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Observation cebd9ac5-417f-4d4a-9c09-fb524437c63b · outbound

This paper cites F-VLM: Open-Vocabulary Object Detection upon Frozen Vision and Language Models.

Unveiling the Underwater World: CLIP Perception Model-Guided Underwater Image Enhancement F-VLM: Open-Vocabulary Object Detection upon Frozen Vision and Language Models

Reference 33

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This paper cites Extract free dense labels from clip,.

Unveiling the Underwater World: CLIP Perception Model-Guided Underwater Image Enhancement Extract free dense labels from clip,

Reference 34

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Observation 75b22962-25b1-4ed1-a00e-f98ef43d720f · outbound

This paper cites Blind image quality assessment via vision-language correspondence: A multitask learning perspective,.

Unveiling the Underwater World: CLIP Perception Model-Guided Underwater Image Enhancement Blind image quality assessment via vision-language correspondence: A multitask learning perspective,

Reference 35

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Observation 2803b646-39bd-4dab-8e80-7c9ba3febf66 · outbound

This paper cites VILA: Learning image aesthetics from user comments with vision-language pretraining,.

Unveiling the Underwater World: CLIP Perception Model-Guided Underwater Image Enhancement VILA: Learning image aesthetics from user comments with vision-language pretraining,

Reference 36

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Observation 54d02222-12eb-4b9a-9df6-fef1650b897a · outbound

This paper cites A reference-free underwater image quality assessment metric in frequency domain,.

Unveiling the Underwater World: CLIP Perception Model-Guided Underwater Image Enhancement A reference-free underwater image quality assessment metric in frequency domain,

Reference 37

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Observation ec380b78-6b0f-4cde-82ab-25621f9fd0e0 · outbound

This paper cites Learning to prompt for vision- language models,.

Unveiling the Underwater World: CLIP Perception Model-Guided Underwater Image Enhancement Learning to prompt for vision- language models,

Reference 39

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This paper cites Conditional prompt learning for vision-language models,.

Unveiling the Underwater World: CLIP Perception Model-Guided Underwater Image Enhancement Conditional prompt learning for vision-language models,

Reference 40

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This paper cites A simple framework for contrastive learning of visual representations,.

Unveiling the Underwater World: CLIP Perception Model-Guided Underwater Image Enhancement A simple framework for contrastive learning of visual representations,

Reference 41

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This paper cites Bootstrap your own latent-a new approach to self-supervised learning,.

Unveiling the Underwater World: CLIP Perception Model-Guided Underwater Image Enhancement Bootstrap your own latent-a new approach to self-supervised learning,

Reference 42

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This paper cites Momentum contrast for unsupervised visual representation learning,.

Unveiling the Underwater World: CLIP Perception Model-Guided Underwater Image Enhancement Momentum contrast for unsupervised visual representation learning,

Reference 43

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Observation addccb51-ec0b-4974-b63f-f9cb39bcb141 · outbound

This paper cites Curriculum learning,.

Unveiling the Underwater World: CLIP Perception Model-Guided Underwater Image Enhancement Curriculum learning,

Reference 44

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This paper cites Contrastive semi- supervised learning for underwater image restoration via reliable bank,.

Unveiling the Underwater World: CLIP Perception Model-Guided Underwater Image Enhancement Contrastive semi- supervised learning for underwater image restoration via reliable bank,

Reference 45

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Observation f014dcf9-0335-4bf2-8ccb-9d1b080feb2e · outbound

This paper cites Underwater image restoration via contrastive learning and a real-world dataset,.

Unveiling the Underwater World: CLIP Perception Model-Guided Underwater Image Enhancement Underwater image restoration via contrastive learning and a real-world dataset,

Reference 46

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Observation 5dd1231f-8ccd-48e3-9d34-2bcf9e2da07e · outbound

This paper cites Denseclip: Language-guided dense prediction with context-aware prompting,.

Unveiling the Underwater World: CLIP Perception Model-Guided Underwater Image Enhancement Denseclip: Language-guided dense prediction with context-aware prompting,

Reference 47

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T05:35:22.637586Z

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Observation c4cd3359-cc33-4718-bf2a-c48c882c4f5d · outbound

This paper cites Natural language processing: State of the art, current trends and challenges,.

Unveiling the Underwater World: CLIP Perception Model-Guided Underwater Image Enhancement Natural language processing: State of the art, current trends and challenges,

Reference 48

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Observation f1573a1f-976c-4b0d-96e3-cca44aa87133 · outbound

This paper cites Human perceptual quality driven underwater image enhancement framework,.

Unveiling the Underwater World: CLIP Perception Model-Guided Underwater Image Enhancement Human perceptual quality driven underwater image enhancement framework,

Reference 49

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T05:35:22.613206Z

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Observation 3d61222d-50ce-431d-a964-96a7fb5a45c1 · outbound

This paper cites A Fusion Adversarial Underwater Image Enhancement Network with a Public Test Dataset.

Unveiling the Underwater World: CLIP Perception Model-Guided Underwater Image Enhancement A Fusion Adversarial Underwater Image Enhancement Network with a Public Test Dataset

Reference 50

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Observation c7eb7fd7-cf66-44d2-a2b2-e6ffb8b70c9e · outbound

This paper cites The unreasonable effectiveness of deep features as a perceptual metric,.

Unveiling the Underwater World: CLIP Perception Model-Guided Underwater Image Enhancement The unreasonable effectiveness of deep features as a perceptual metric,

Reference 51

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Observation 5ee56c71-ef03-4d81-8719-c3db80b4b338 · outbound

This paper cites An underwater color image quality evaluation metric,.

Unveiling the Underwater World: CLIP Perception Model-Guided Underwater Image Enhancement An underwater color image quality evaluation metric,

Reference 52

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Observation d6878d38-8280-4218-8c13-65b01d17190f · outbound

This paper cites Human-visual-system-inspired underwater image quality measures,.

Unveiling the Underwater World: CLIP Perception Model-Guided Underwater Image Enhancement Human-visual-system-inspired underwater image quality measures,

Reference 53

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This paper cites Transmission estimation in underwater single images,.

Unveiling the Underwater World: CLIP Perception Model-Guided Underwater Image Enhancement Transmission estimation in underwater single images,

Reference 54

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T05:35:22.571490Z

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Observation df238265-129b-4ded-93ca-1baecba261e5 · outbound

This paper cites Under- water image enhancement via minimal color loss and locally adaptive contrast enhancement,.

Unveiling the Underwater World: CLIP Perception Model-Guided Underwater Image Enhancement Under- water image enhancement via minimal color loss and locally adaptive contrast enhancement,

Reference 55

Resolution: unresolved; no resolver link, observed 2026-08-16T05:35:22.140221Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4cd3cff7-3bb5-4249-a8d0-e7b6ec9fdd0c · outbound

This paper cites Fast underwater image enhancement for improved visual perception,.

Unveiling the Underwater World: CLIP Perception Model-Guided Underwater Image Enhancement Fast underwater image enhancement for improved visual perception,

Reference 56

Resolution: unresolved; no resolver link, observed 2026-08-16T05:35:22.144487Z

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Unavailable: canonical work link unavailable.

Observation 317b5aeb-4cb2-488a-8cc9-5e4f2f1941f2 · outbound

This paper cites Subjective and objective de-raining quality assessment towards authentic rain image,.

Unveiling the Underwater World: CLIP Perception Model-Guided Underwater Image Enhancement Subjective and objective de-raining quality assessment towards authentic rain image,

Reference 57

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T05:35:22.538949Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 4d40e179-7c26-4928-92be-b910e8fe8bf7 · outbound

This paper cites PUGAN: Physical model-guided underwater image en- hancement using gan with dual-discriminators,.

Unveiling the Underwater World: CLIP Perception Model-Guided Underwater Image Enhancement PUGAN: Physical model-guided underwater image en- hancement using gan with dual-discriminators,

Reference 58

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T05:35:22.524408Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation f792d9d2-8589-45d7-b79e-9e2eb6e7a605 · outbound

This paper cites SVAM: Saliency-guided Visual Attention Modeling by Autonomous Underwater Robots.

Unveiling the Underwater World: CLIP Perception Model-Guided Underwater Image Enhancement SVAM: Saliency-guided Visual Attention Modeling by Autonomous Underwater Robots

Reference 59

Resolution: unresolved; no resolver link, observed 2026-08-16T05:35:22.157872Z

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Observation 90de3900-5359-43e7-b1b3-89f59864431b · outbound

This paper cites Re- inforced swin-convs transformer for simultaneous underwater sensing scene image enhancement and super-resolution,.

Unveiling the Underwater World: CLIP Perception Model-Guided Underwater Image Enhancement Re- inforced swin-convs transformer for simultaneous underwater sensing scene image enhancement and super-resolution,

Reference 60

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T05:35:22.509997Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 4d5e2609-ddcf-4a28-ad7a-6dbe6d4bbce2 · outbound

This paper cites UW- CycleGAN: Model-driven cyclegan for underwater image restoration,.

Unveiling the Underwater World: CLIP Perception Model-Guided Underwater Image Enhancement UW- CycleGAN: Model-driven cyclegan for underwater image restoration,

Reference 61

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T05:35:22.494354Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 117092ae-6b23-40f6-a83e-40adc572295c · outbound

This paper cites Iterative prompt learn- ing for unsupervised backlit image enhancement,.

Unveiling the Underwater World: CLIP Perception Model-Guided Underwater Image Enhancement Iterative prompt learn- ing for unsupervised backlit image enhancement,

Reference 62

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T05:35:22.477890Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation f768f8b1-71bf-40a8-ba67-a7bed0cc2bdf · outbound

This paper cites Unsu- pervised underwater image restoration: From a homology perspective,.

Unveiling the Underwater World: CLIP Perception Model-Guided Underwater Image Enhancement Unsu- pervised underwater image restoration: From a homology perspective,

Reference 63

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T05:35:22.462693Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 32e8ccb0-6520-4570-a88f-e44a60cc75fc · outbound

This paper cites Image enhancement by histogram transformation,.

Unveiling the Underwater World: CLIP Perception Model-Guided Underwater Image Enhancement Image enhancement by histogram transformation,

Reference 64

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T05:35:22.447349Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation fcda5f03-1586-4db1-90b9-0aa7dff02fcb · outbound

This paper cites Underwater image enhancement quality evaluation: Benchmark dataset and objective met- ric,.

Unveiling the Underwater World: CLIP Perception Model-Guided Underwater Image Enhancement Underwater image enhancement quality evaluation: Benchmark dataset and objective met- ric,

Reference 65

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T05:35:22.739301Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 10eeb4e0-baf2-410b-9888-07232757de42 · outbound

This paper cites MirrorDiffusion: Stabilizing diffusion process in zero-shot image translation by prompts redescription and beyond,.

Unveiling the Underwater World: CLIP Perception Model-Guided Underwater Image Enhancement MirrorDiffusion: Stabilizing diffusion process in zero-shot image translation by prompts redescription and beyond,

Reference 66

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T05:35:22.432128Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 3162cbcd-b69e-4891-af54-1f0df71e69df · outbound

This paper cites Exploring negatives in contrastive learning for unpaired image-to-image translation,.

Unveiling the Underwater World: CLIP Perception Model-Guided Underwater Image Enhancement Exploring negatives in contrastive learning for unpaired image-to-image translation,

Reference 67

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T05:35:22.416383Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 441ada31-2d96-403e-99e3-cd5a9aea9ffe · outbound

This paper cites Perceptual losses for real-time style transfer and super-resolution,.

Unveiling the Underwater World: CLIP Perception Model-Guided Underwater Image Enhancement Perceptual losses for real-time style transfer and super-resolution,

Reference 68

Resolution: unresolved; no resolver link, observed 2026-08-16T05:35:22.194432Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f6efe85c-2c54-4f08-a386-efa2959ee6c6 · outbound

This paper cites AUV navigation and localiza- tion: A review,.

Unveiling the Underwater World: CLIP Perception Model-Guided Underwater Image Enhancement AUV navigation and localiza- tion: A review,

Reference 69

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T05:35:22.391787Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation fbde6d4c-87d5-42ca-a687-da0d4ab73050 · outbound

This paper cites RRNet: Re- lational reasoning network with parallel multiscale attention for salient object detection in optical remote sensing images,.

Unveiling the Underwater World: CLIP Perception Model-Guided Underwater Image Enhancement RRNet: Re- lational reasoning network with parallel multiscale attention for salient object detection in optical remote sensing images,

Reference 70

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T05:35:22.377441Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 525cb37a-90ee-4883-9252-b042214abdc9 · outbound

This paper cites A reinforcement learning paradigm of configuring visual enhancement for object detection in underwater scenes,.

Unveiling the Underwater World: CLIP Perception Model-Guided Underwater Image Enhancement A reinforcement learning paradigm of configuring visual enhancement for object detection in underwater scenes,

Reference 71

Resolution: unresolved; no resolver link, observed 2026-08-16T05:35:22.206166Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 226d1158-dac1-4292-80f7-1d9cb8ce197d · outbound

This paper cites Nested network with two-stream pyramid for salient object detection in optical remote sensing images,.

Unveiling the Underwater World: CLIP Perception Model-Guided Underwater Image Enhancement Nested network with two-stream pyramid for salient object detection in optical remote sensing images,

Reference 72

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T05:35:22.352113Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation fcae3e4b-0a7c-4fa8-8526-77cce794d392 · outbound

This paper cites Diving deeper into underwater image enhance- ment: A survey,.

Unveiling the Underwater World: CLIP Perception Model-Guided Underwater Image Enhancement Diving deeper into underwater image enhance- ment: A survey,

Reference 73

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T05:35:22.336306Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation e3655397-bdbc-4074-9831-d37d8c6e7c0d · outbound

This paper cites Underwater image enhancement via adaptive group attention-based multiscale cascade transformer,.

Unveiling the Underwater World: CLIP Perception Model-Guided Underwater Image Enhancement Underwater image enhancement via adaptive group attention-based multiscale cascade transformer,

Reference 74

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T05:35:22.321010Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation bf103bc1-a68f-4da6-8108-a927e8d34b03 · outbound

This paper cites Multiscale underwater image enhancement in rgb and hsv color spaces,.

Unveiling the Underwater World: CLIP Perception Model-Guided Underwater Image Enhancement Multiscale underwater image enhancement in rgb and hsv color spaces,

Reference 75

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T05:35:22.305481Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

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