Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-11T04:35:18.776399Z
Paper Citation Record · LEDGER
As of 19 August 2026, this Paper Citation Record lists 65 of 65 outbound references and 2 inbound Pith citation observations for arXiv:2412.18774.
A citation records a reference. It does not transfer a finding from one paper to another.
Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-11T04:35:18.776399Z
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-19T06:32:44.657259+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-06T21:35:10.202236Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-07-03T10:17:57.673134Z
65 of 65 outbound references displayed
External citation measurements
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Observation ae2e64e6-3e56-427b-a21f-6051eba10d85 · outbound
Embodied Image Quality Assessment for Robotic Intelligence A Survey on Image Quality Assessment: Insights, Analysis, and Future Outlook
Reference 1
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Observation 36017fde-5bb2-4fa2-9956-8b7a2174071a · outbound
Embodied Image Quality Assessment for Robotic Intelligence No-reference image quality assessment: Obtain mos from image quality score distribution,
Reference 2
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Embodied Image Quality Assessment for Robotic Intelligence Study of subjective and objective naturalness assessment of ai-generated images,
Reference 3
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Observation 4fdc224d-5b09-42ac-80a9-5b503e02e9d2 · outbound
Embodied Image Quality Assessment for Robotic Intelligence Single image dehazing using fuzzy region segmentation and haze density decomposition,
Reference 4
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Embodied Image Quality Assessment for Robotic Intelligence Dual degradation representation for joint deraining and low-light enhancement in the dark,
Reference 5
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Embodied Image Quality Assessment for Robotic Intelligence Omni-deblurring: Capturing omni-range context for image deblurring,
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Observation 268ef3be-90a1-4bb9-935d-4a20f76da9d9 · outbound
Embodied Image Quality Assessment for Robotic Intelligence A reference-free quality enhancement framework for low-quality fundus images,
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Embodied Image Quality Assessment for Robotic Intelligence Synergetic assess- ment of quality and aesthetic: Approach and comprehensive benchmark dataset,
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Embodied Image Quality Assessment for Robotic Intelligence Image quality assess- ment: from error visibility to structural similarity,
Reference 9
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Observation 3a3ed726-c3f7-497b-9f0d-7152edca3f89 · outbound
Embodied Image Quality Assessment for Robotic Intelligence Visual importance pooling for image quality assessment,
Reference 10
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Embodied Image Quality Assessment for Robotic Intelligence Information content weighting for perceptual image quality assessment,
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Embodied Image Quality Assessment for Robotic Intelligence Fsim: A feature similarity index for image quality assessment,
Reference 12
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Observation c4bebe21-2cf0-4a4c-a553-9e86ab4b443c · outbound
Embodied Image Quality Assessment for Robotic Intelligence Gradient magnitude similarity deviation: A highly efficient perceptual image quality index,
Reference 13
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Embodied Image Quality Assessment for Robotic Intelligence Deep learning of human visual sensitivity in image quality assessment framework,
Reference 14
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Observation d64ea3d6-a710-4ce1-b1a2-7f87ca6ab44d · outbound
Embodied Image Quality Assessment for Robotic Intelligence Deep neural networks for no-reference and full-reference image quality assessment,
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Observation e223cd4b-b7c5-4275-8b07-f427a828cf10 · outbound
Embodied Image Quality Assessment for Robotic Intelligence A psychovisual quality metric in free-energy principle,
Reference 16
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Observation d58ab94f-80ea-49f2-bb3a-543493979811 · outbound
Embodied Image Quality Assessment for Robotic Intelligence Blind image quality assessment: From natural scene statistics to perceptual quality,
Reference 17
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Observation a399c2c2-436b-4a4b-881c-0bce589672b4 · outbound
Embodied Image Quality Assessment for Robotic Intelligence Blind image quality assessment based on high order statistics aggregation,
Reference 18
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Observation 5cb7ad37-fcb0-44c8-9149-2790a1cb1c56 · outbound
Embodied Image Quality Assessment for Robotic Intelligence Metaiqa: Deep meta- learning for no-reference image quality assessment,
Reference 19
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Observation a90d7dae-7ed7-4036-84d7-da03075d9051 · outbound
Embodied Image Quality Assessment for Robotic Intelligence Convolutional neural networks for no-reference image quality assessment,
Reference 20
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Observation 0e7b2526-e834-4056-b1bb-e4a7cb9454b3 · outbound
Embodied Image Quality Assessment for Robotic Intelligence A statistical evaluation of recent full reference image quality assessment algorithms,
Reference 21
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Observation b21d54da-0b21-4638-aa55-6df2e850de6a · outbound
Embodied Image Quality Assessment for Robotic Intelligence Kadid-10k: A large-scale artificially distorted iqa database,
Reference 22
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Observation 3eadc8e0-9cff-456c-9441-96fc1e64fe20 · outbound
Embodied Image Quality Assessment for Robotic Intelligence Massive online crowdsourced study of subjective and objective picture quality,
Reference 23
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Observation 62ec3a5d-79fc-4e24-8d32-a530d57c7c0a · outbound
Embodied Image Quality Assessment for Robotic Intelligence Koniq-10k: An ecologically valid database for deep learning of blind image quality assessment,
Reference 24
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Embodied Image Quality Assessment for Robotic Intelligence Q-bench ++: A benchmark for multi-modal foundation models on low-level vision from single images to pairs,
Reference 25
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Observation 0aa943ba-7e61-4afd-80bb-95086327d200 · outbound
Embodied Image Quality Assessment for Robotic Intelligence Agiqa-3k: An open database for ai-generated image quality assessment,
Reference 26
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Observation e3b15c02-c11c-43d2-9ec6-3f2ac0deb19c · outbound
Embodied Image Quality Assessment for Robotic Intelligence A-Bench: Are LMMs Masters at Evaluating AI-generated Images?
Reference 27
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Observation 4de330b1-a7f3-451f-9ddd-1f1d7888bd1d · outbound
Embodied Image Quality Assessment for Robotic Intelligence CMC-Bench: Towards a New Paradigm of Visual Signal Compression
Reference 28
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Observation 2512d487-4e3e-4093-878f-f445fde1b76a · outbound
Embodied Image Quality Assessment for Robotic Intelligence R-bench: Are your large multimodal model robust to real-world corruptions?
Reference 29
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Observation 649755c9-5138-454b-a563-112a1da8edf7 · outbound
Embodied Image Quality Assessment for Robotic Intelligence Aligning cyber space with physical world: A comprehensive survey on embodied ai,
Reference 30
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Observation 9d91702a-de49-4612-b51d-c2a6481a2b93 · outbound
Embodied Image Quality Assessment for Robotic Intelligence Real-time recognition of team be- haviors by multisensory graph-embedded robot learning,
Reference 31
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Observation f7512676-a6fc-4239-bb88-b3e2f855321b · outbound
Embodied Image Quality Assessment for Robotic Intelligence Analysis of an all- terrain tracked robot with innovative suspension system,
Reference 32
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Observation a20cdf72-5a99-4e52-ae2c-0793aace6c6a · outbound
Embodied Image Quality Assessment for Robotic Intelligence Swarm of micro flying robots in the wild,
Reference 33
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Observation 34ff92dd-5254-46c1-aaef-6bc7865d9470 · outbound
Embodied Image Quality Assessment for Robotic Intelligence Scientific exploration of chal- lenging planetary analog environments with a team of legged robots,
Reference 34
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Observation e6e15744-dea1-4306-9137-7d2608878499 · outbound
Embodied Image Quality Assessment for Robotic Intelligence Advancements in humanoid robots: A comprehensive review and future prospects,
Reference 35
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Observation 29cb3cfd-d86c-4662-ac0b-b8767f4ee639 · outbound
Embodied Image Quality Assessment for Robotic Intelligence Implicit coordination for 3d underwater collective behaviors in a fish-inspired robot swarm,
Reference 36
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Observation ac16e205-9b8f-4286-8761-14dd793cb6d8 · outbound
Embodied Image Quality Assessment for Robotic Intelligence The franka emika robot: A reference platform for robotics research and education,
Reference 37
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Observation cc85886b-e83e-41f1-941c-0636d16c3129 · outbound
Embodied Image Quality Assessment for Robotic Intelligence Bas optimized elm for kuka iiwa robot learning,
Reference 38
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Observation 752d97cf-1bef-4f32-8c86-4bc9a2081a6f · outbound
Embodied Image Quality Assessment for Robotic Intelligence Isaac Gym: High Performance GPU-Based Physics Simulation For Robot Learning
Reference 39
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Observation be5cde5f-7584-4915-9139-ac406cd2d157 · outbound
Embodied Image Quality Assessment for Robotic Intelligence Design and use paradigms for gazebo, an open-source multi-robot simulator,
Reference 40
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Observation 2d6ca9e9-06da-41dd-9098-47db8f965b4f · outbound
Embodied Image Quality Assessment for Robotic Intelligence Pybullet, a python module for physics simulation for games, robotics and machine learning,
Reference 41
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Observation 35066bc1-a63c-4196-8c90-e35bbedc7331 · outbound
Embodied Image Quality Assessment for Robotic Intelligence AI2-THOR: An Interactive 3D Environment for Visual AI
Reference 42
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Observation 2b3f61b3-0ef5-4fba-b410-e5cbea8a75bd · outbound
Embodied Image Quality Assessment for Robotic Intelligence Habitat: A platform for embodied ai research,
Reference 43
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Observation 2c102028-8820-4ea1-9537-ad2aa0c7bd2f · outbound
Embodied Image Quality Assessment for Robotic Intelligence Sapien: A simulated part-based interactive environment,
Reference 44
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Observation 52fd0e60-c7f8-45f9-8ca2-544d5d5bb11c · outbound
Embodied Image Quality Assessment for Robotic Intelligence Proximal Policy Optimization Algorithms
Reference 45
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Observation 8eccfaeb-389b-4590-8dcc-8619b0bbd25f · outbound
Embodied Image Quality Assessment for Robotic Intelligence Soft actor-critic: Off- policy maximum entropy deep reinforcement learning with a stochastic actor,
Reference 46
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Observation f528b67d-29d4-4956-9509-e494dcabab73 · outbound
Embodied Image Quality Assessment for Robotic Intelligence TD-MPC2: Scalable, Robust World Models for Continuous Control
Reference 47
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Observation a6ff56d1-9ba6-46cc-aee9-42b714e8306f · outbound
Embodied Image Quality Assessment for Robotic Intelligence ManiSkill3: GPU Parallelized Robotics Simulation and Rendering for Generalizable Embodied AI
Reference 48
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Observation 7a43003d-0ee2-401f-b92e-9419774fb17d · outbound
Embodied Image Quality Assessment for Robotic Intelligence Deep residual learning for image recognition,
Reference 49
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Observation d3a6b945-e863-49a5-bfee-6017e97a30c5 · outbound
Embodied Image Quality Assessment for Robotic Intelligence Path aggregation network for instance segmentation,
Reference 50
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Observation 0657dd87-2911-4d18-b741-643f680e35ca · outbound
Embodied Image Quality Assessment for Robotic Intelligence Cbam: Convolutional block attention module,
Reference 51
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Embodied Image Quality Assessment for Robotic Intelligence Attentions help cnns see better: Attention-based hybrid image quality 13 assessment network,
Reference 52
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Reference 53
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Observation 8932b8b5-3db5-4a05-a982-9087b29d0cb0 · outbound
Embodied Image Quality Assessment for Robotic Intelligence Learning conditional knowledge distillation for degraded-reference image quality assessment,
Reference 54
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Reference 55
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Observation 9c4adea3-6e5c-44cd-8f1d-558208b96a1c · outbound
Embodied Image Quality Assessment for Robotic Intelligence The unreasonable effectiveness of deep features as a perceptual metric,
Reference 56
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Observation de5ec14b-5025-47f5-9254-dcf1f0d7aed9 · outbound
Embodied Image Quality Assessment for Robotic Intelligence Topiq: A top-down approach from semantics to distortions for image quality assessment,
Reference 57
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Embodied Image Quality Assessment for Robotic Intelligence Perceptual image quality assessment with transformers,
Reference 58
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Reference 60
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Embodied Image Quality Assessment for Robotic Intelligence Maniqa: Multi-dimension attention network for no-reference image quality assessment,
Reference 61
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Observation b138df14-11c3-4139-9d84-674fd8cda315 · outbound
Embodied Image Quality Assessment for Robotic Intelligence Blind image quality assessment via transformer predicted error map and perceptual quality token,
Reference 62
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Observation 24aff8ea-9465-4e3d-b4cb-09c40c64375f · outbound
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Reference 63
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Observation 60d9d947-b5c9-49ff-aaed-4b4de1616854 · outbound
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Observation 9e6b9bea-112c-4dde-a691-fe55d30b9142 · outbound
Embodied Image Quality Assessment for Robotic Intelligence IQA-PyTorch: Pytorch toolbox for image quality assessment,
Reference 65
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Observation 5da25d0b-e30d-4d8a-b4ea-8f2684db844c · inbound
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