Paper Citation Record · LEDGER

APRIL-GAN: A Zero-/Few-Shot Anomaly Classification and Segmentation Method for CVPR 2023 VAND Workshop Challenge Tracks 1&2: 1st Place on Zero-shot AD and 4th Place on Few-shot AD

As of 7 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 30 inbound Pith citation observations for arXiv:2305.17382.

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

pith.paper-citation-record.v1
2305.17382 v3

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measured 0 of 0 reference resolution

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measured 30 of 30 standing notices

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Source: scholarly_work_events, retraction_status_cache, observed 2026-08-07T06:34:17.273281+00:00

measured 30 of 30 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T14:10:33.642713Z

measured 0 of 1 external citation measurements

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Source: arxiv_reference, observed 2026-07-04T19:50:10.587152Z

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Pith citing papers

Observation 5a9499d4-29b7-4355-b9e6-5d9fb7e10a6f · inbound

SuperAD: A Training-free Anomaly Classification and Segmentation Method for CVPR 2025 VAND 3.0 Workshop Challenge Track 1: Adapt & Detect cites this paper.

SuperAD: A Training-free Anomaly Classification and Segmentation Method for CVPR 2025 VAND 3.0 Workshop Challenge Track 1: Adapt & Detect APRIL-GAN: A Zero-/Few-Shot Anomaly Classification and Segmentation Method for CVPR 2023 VAND Workshop Challenge Tracks 1&2: 1st Place on Zero-shot AD and 4th Place on Few-shot AD

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-07T14:10:33.642713Z

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Observation f690d02c-9e1d-4312-8751-1142da019eab · inbound

INP-Former++: Advancing Universal Anomaly Detection via Intrinsic Normal Prototypes and Residual Learning cites this paper.

INP-Former++: Advancing Universal Anomaly Detection via Intrinsic Normal Prototypes and Residual Learning APRIL-GAN: A Zero-/Few-Shot Anomaly Classification and Segmentation Method for CVPR 2023 VAND Workshop Challenge Tracks 1&2: 1st Place on Zero-shot AD and 4th Place on Few-shot AD

Reference 80

Resolution: unresolved; no resolver link, observed 2026-08-07T11:03:11.260556Z

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Observation c1316dc7-c99e-4000-89b3-40cb32fcd2ee · inbound

IQE-CLIP: Instance-aware Query Embedding for Zero-/Few-shot Anomaly Detection in Medical Domain cites this paper.

IQE-CLIP: Instance-aware Query Embedding for Zero-/Few-shot Anomaly Detection in Medical Domain APRIL-GAN: A Zero-/Few-Shot Anomaly Classification and Segmentation Method for CVPR 2023 VAND Workshop Challenge Tracks 1&2: 1st Place on Zero-shot AD and 4th Place on Few-shot AD

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-07T04:28:34.693002Z

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Observation 639543f5-bcc6-4192-b998-3228c196ed5f · inbound

Anomaly Object Segmentation with Vision-Language Models for Steel Scrap Recycling cites this paper.

Anomaly Object Segmentation with Vision-Language Models for Steel Scrap Recycling APRIL-GAN: A Zero-/Few-Shot Anomaly Classification and Segmentation Method for CVPR 2023 VAND Workshop Challenge Tracks 1&2: 1st Place on Zero-shot AD and 4th Place on Few-shot AD

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-07T00:41:25.974727Z

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Observation de2078b0-4ae2-4e30-ad93-9c44b2177ce7 · inbound

StackCLIP: Clustering-Driven Stacked Prompt in Zero-Shot Industrial Anomaly Detection cites this paper.

StackCLIP: Clustering-Driven Stacked Prompt in Zero-Shot Industrial Anomaly Detection APRIL-GAN: A Zero-/Few-Shot Anomaly Classification and Segmentation Method for CVPR 2023 VAND Workshop Challenge Tracks 1&2: 1st Place on Zero-shot AD and 4th Place on Few-shot AD

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-06T21:43:26.960856Z

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Observation c50e234c-ec7b-4851-b882-889c1081381e · inbound

MadCLIP: Few-shot Medical Anomaly Detection with CLIP cites this paper.

MadCLIP: Few-shot Medical Anomaly Detection with CLIP APRIL-GAN: A Zero-/Few-Shot Anomaly Classification and Segmentation Method for CVPR 2023 VAND Workshop Challenge Tracks 1&2: 1st Place on Zero-shot AD and 4th Place on Few-shot AD

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-06T21:35:08.234445Z

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Observation e003e859-f2ac-44fd-97b9-09d171ad3b59 · inbound

MADPOT: Medical Anomaly Detection with CLIP Adaptation and Partial Optimal Transport cites this paper.

MADPOT: Medical Anomaly Detection with CLIP Adaptation and Partial Optimal Transport APRIL-GAN: A Zero-/Few-Shot Anomaly Classification and Segmentation Method for CVPR 2023 VAND Workshop Challenge Tracks 1&2: 1st Place on Zero-shot AD and 4th Place on Few-shot AD

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-06T19:01:21.731360Z

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Observation 5850c8cc-022a-4b39-8f94-510d4528ef6b · inbound

Bridge Feature Matching and Cross-Modal Alignment with Mutual-filtering for Zero-shot Anomaly Detection cites this paper.

Bridge Feature Matching and Cross-Modal Alignment with Mutual-filtering for Zero-shot Anomaly Detection APRIL-GAN: A Zero-/Few-Shot Anomaly Classification and Segmentation Method for CVPR 2023 VAND Workshop Challenge Tracks 1&2: 1st Place on Zero-shot AD and 4th Place on Few-shot AD

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-06T17:27:14.628862Z

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Observation 60df2d7b-edd8-4f19-b2a4-ac7ffe62e6bf · inbound

A Comprehensive Survey for Real-World Industrial Defect Detection: Challenges, Approaches, and Prospects cites this paper.

A Comprehensive Survey for Real-World Industrial Defect Detection: Challenges, Approaches, and Prospects APRIL-GAN: A Zero-/Few-Shot Anomaly Classification and Segmentation Method for CVPR 2023 VAND Workshop Challenge Tracks 1&2: 1st Place on Zero-shot AD and 4th Place on Few-shot AD

Reference 194

Resolution: unresolved; no resolver link, observed 2026-08-06T17:21:52.435384Z

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Observation a193bb76-c0ae-4de1-b7a2-2538afae9188 · inbound

AF-CLIP: Zero-Shot Anomaly Detection via Anomaly-Focused CLIP Adaptation cites this paper.

AF-CLIP: Zero-Shot Anomaly Detection via Anomaly-Focused CLIP Adaptation APRIL-GAN: A Zero-/Few-Shot Anomaly Classification and Segmentation Method for CVPR 2023 VAND Workshop Challenge Tracks 1&2: 1st Place on Zero-shot AD and 4th Place on Few-shot AD

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-06T13:56:55.690231Z

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Observation e11a5d4e-6e34-4113-b111-6765c5febed4 · inbound

IADGPT: Unified LVLM for Few-Shot Industrial Anomaly Detection, Localization, and Reasoning via In-Context Learning cites this paper.

IADGPT: Unified LVLM for Few-Shot Industrial Anomaly Detection, Localization, and Reasoning via In-Context Learning APRIL-GAN: A Zero-/Few-Shot Anomaly Classification and Segmentation Method for CVPR 2023 VAND Workshop Challenge Tracks 1&2: 1st Place on Zero-shot AD and 4th Place on Few-shot AD

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-05T20:20:12.383725Z

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Observation e2ce198e-f9d7-4d71-bde9-707db797270c · inbound

DictAS: A Framework for Class-Generalizable Few-Shot Anomaly Segmentation via Dictionary Lookup cites this paper.

DictAS: A Framework for Class-Generalizable Few-Shot Anomaly Segmentation via Dictionary Lookup APRIL-GAN: A Zero-/Few-Shot Anomaly Classification and Segmentation Method for CVPR 2023 VAND Workshop Challenge Tracks 1&2: 1st Place on Zero-shot AD and 4th Place on Few-shot AD

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-05T18:59:07.580832Z

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Observation 943bdf82-48d2-45c2-b7cb-52496241ed87 · inbound

Generative Model-Based Feature Attention Module for Video Action Analysis cites this paper.

Generative Model-Based Feature Attention Module for Video Action Analysis APRIL-GAN: A Zero-/Few-Shot Anomaly Classification and Segmentation Method for CVPR 2023 VAND Workshop Challenge Tracks 1&2: 1st Place on Zero-shot AD and 4th Place on Few-shot AD

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-05T19:03:27.539289Z

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Observation 70198286-67da-4ce5-a02a-93fc25977503 · inbound

TMUAD: Enhancing Logical Capabilities in Unified Anomaly Detection Models with a Text Memory Bank cites this paper.

TMUAD: Enhancing Logical Capabilities in Unified Anomaly Detection Models with a Text Memory Bank APRIL-GAN: A Zero-/Few-Shot Anomaly Classification and Segmentation Method for CVPR 2023 VAND Workshop Challenge Tracks 1&2: 1st Place on Zero-shot AD and 4th Place on Few-shot AD

Reference 61

Resolution: unresolved; no resolver link, observed 2026-08-05T14:01:40.849367Z

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Observation 31491206-8df0-438d-942a-19a8872aee7a · inbound

Action Hints: Semantic Typicality and Context Uniqueness for Generalizable Skeleton-based Video Anomaly Detection cites this paper.

Action Hints: Semantic Typicality and Context Uniqueness for Generalizable Skeleton-based Video Anomaly Detection APRIL-GAN: A Zero-/Few-Shot Anomaly Classification and Segmentation Method for CVPR 2023 VAND Workshop Challenge Tracks 1&2: 1st Place on Zero-shot AD and 4th Place on Few-shot AD

Reference 31

Resolution: verified exact; arxiv_id, observed 2026-05-18T17:16:40.107022Z

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Observation 5f55ce7a-b7e7-460d-bec8-b4d1f98dcb65 · inbound

Advancing Metallic Surface Defect Detection via Anomaly-Guided Pretraining on a Large Industrial Dataset cites this paper.

Advancing Metallic Surface Defect Detection via Anomaly-Guided Pretraining on a Large Industrial Dataset APRIL-GAN: A Zero-/Few-Shot Anomaly Classification and Segmentation Method for CVPR 2023 VAND Workshop Challenge Tracks 1&2: 1st Place on Zero-shot AD and 4th Place on Few-shot AD

Reference 43

Resolution: unresolved; no resolver link, observed 2026-08-04T15:43:10.138007Z

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Observation dea8005b-8e33-427a-b451-92537a0e8a37 · inbound

MuSc-V2: Zero-Shot Multimodal Industrial Anomaly Classification and Segmentation with Mutual Scoring of Unlabeled Samples cites this paper.

MuSc-V2: Zero-Shot Multimodal Industrial Anomaly Classification and Segmentation with Mutual Scoring of Unlabeled Samples APRIL-GAN: A Zero-/Few-Shot Anomaly Classification and Segmentation Method for CVPR 2023 VAND Workshop Challenge Tracks 1&2: 1st Place on Zero-shot AD and 4th Place on Few-shot AD

Reference 16

Resolution: verified exact; arxiv_id, observed 2026-05-17T23:00:25.934564Z

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No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation d5d5101f-f506-4c8f-8d72-246140ce0b2b · inbound

Defect-aware Hybrid Prompt Optimization via Progressive Tuning for Zero-Shot Multi-type Anomaly Detection and Segmentation cites this paper.

Defect-aware Hybrid Prompt Optimization via Progressive Tuning for Zero-Shot Multi-type Anomaly Detection and Segmentation APRIL-GAN: A Zero-/Few-Shot Anomaly Classification and Segmentation Method for CVPR 2023 VAND Workshop Challenge Tracks 1&2: 1st Place on Zero-shot AD and 4th Place on Few-shot AD

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-03T17:28:39.233436Z

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Observation 275840c5-83bb-49f2-b314-e0abfe480cf8 · inbound

HLGFA: High-Low Resolution Guided Feature Alignment for Unsupervised Anomaly Detection cites this paper.

HLGFA: High-Low Resolution Guided Feature Alignment for Unsupervised Anomaly Detection APRIL-GAN: A Zero-/Few-Shot Anomaly Classification and Segmentation Method for CVPR 2023 VAND Workshop Challenge Tracks 1&2: 1st Place on Zero-shot AD and 4th Place on Few-shot AD

Reference 2

Resolution: verified exact; arxiv_id, observed 2026-05-16T03:07:11.849660Z

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Observation a53a8cac-f8af-4b9c-8c95-181ac35177c2 · inbound

Training-Free Zero-Shot Anomaly Detection in 3D Brain MRI with 2D Foundation Models cites this paper.

Training-Free Zero-Shot Anomaly Detection in 3D Brain MRI with 2D Foundation Models APRIL-GAN: A Zero-/Few-Shot Anomaly Classification and Segmentation Method for CVPR 2023 VAND Workshop Challenge Tracks 1&2: 1st Place on Zero-shot AD and 4th Place on Few-shot AD

Reference 2024

Resolution: unresolved; no resolver link, observed 2026-08-02T22:59:24.192836Z

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Observation 5f07db58-bfa2-43ab-b619-f3e13f8b30e6 · inbound

Closed form perturbative relativistic modifications to wave-packet dynamics in the quantum harmonic oscillator cites this paper.

Closed form perturbative relativistic modifications to wave-packet dynamics in the quantum harmonic oscillator APRIL-GAN: A Zero-/Few-Shot Anomaly Classification and Segmentation Method for CVPR 2023 VAND Workshop Challenge Tracks 1&2: 1st Place on Zero-shot AD and 4th Place on Few-shot AD

Reference 10

Resolution: unresolved; no resolver link, observed 2026-07-15T12:56:18.518533Z

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Observation fbeb85a0-ea34-49c8-8204-5f5384ca5f29 · inbound

Hypergraph-Enhanced Training-Free and Language-Free Few-Shot Anomaly Detection cites this paper.

Hypergraph-Enhanced Training-Free and Language-Free Few-Shot Anomaly Detection APRIL-GAN: A Zero-/Few-Shot Anomaly Classification and Segmentation Method for CVPR 2023 VAND Workshop Challenge Tracks 1&2: 1st Place on Zero-shot AD and 4th Place on Few-shot AD

Reference 4

Resolution: metadata mismatch; arxiv_id, observed 2026-05-12T05:26:25.505514Z

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Observation 55833702-964a-4884-a45b-acbbb4137e08 · inbound

Res$^2$CLIP: Few-Shot Generalist Anomaly Detection with Residual-to-Residual Alignment cites this paper.

Res$^2$CLIP: Few-Shot Generalist Anomaly Detection with Residual-to-Residual Alignment APRIL-GAN: A Zero-/Few-Shot Anomaly Classification and Segmentation Method for CVPR 2023 VAND Workshop Challenge Tracks 1&2: 1st Place on Zero-shot AD and 4th Place on Few-shot AD

Reference 4

Resolution: verified exact; arxiv_id, observed 2026-05-20T18:58:53.911719Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 005b066f-03e1-43d3-90ae-30fe222a300e · inbound

Towards Active Real-to-Twin Inspection: A New Paradigm for Zero-Shot Anomaly Detection cites this paper.

Towards Active Real-to-Twin Inspection: A New Paradigm for Zero-Shot Anomaly Detection APRIL-GAN: A Zero-/Few-Shot Anomaly Classification and Segmentation Method for CVPR 2023 VAND Workshop Challenge Tracks 1&2: 1st Place on Zero-shot AD and 4th Place on Few-shot AD

Reference 3

Resolution: verified exact; arxiv_id, observed 2026-06-29T23:14:02.021467Z

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Observation ad05b736-d13d-4212-89e2-df90a727e521 · inbound

EntroAD: Structural Entropy-Guided Prompt Adaptation for Zero-Shot Anomaly Detection cites this paper.

EntroAD: Structural Entropy-Guided Prompt Adaptation for Zero-Shot Anomaly Detection APRIL-GAN: A Zero-/Few-Shot Anomaly Classification and Segmentation Method for CVPR 2023 VAND Workshop Challenge Tracks 1&2: 1st Place on Zero-shot AD and 4th Place on Few-shot AD

Reference 4

Resolution: verified exact; arxiv_id, observed 2026-06-29T13:13:27.311565Z

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No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 6627f5eb-99ea-46f9-9d06-fca7ce92a00d · inbound

AnomalyAgent: Training-Free Agentic Models for Zero-/Few-Shot Anomaly Detection cites this paper.

AnomalyAgent: Training-Free Agentic Models for Zero-/Few-Shot Anomaly Detection APRIL-GAN: A Zero-/Few-Shot Anomaly Classification and Segmentation Method for CVPR 2023 VAND Workshop Challenge Tracks 1&2: 1st Place on Zero-shot AD and 4th Place on Few-shot AD

Reference 7

Resolution: verified exact; arxiv_id, observed 2026-06-29T08:13:14.931884Z

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No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation bb9e64dc-ec91-477b-993e-9f2ae33a049c · inbound

CoGeoAD: Hierarchical Color-Geometric Fusion with Multi-View Attention for Zero-Shot 3D Anomaly Detection cites this paper.

CoGeoAD: Hierarchical Color-Geometric Fusion with Multi-View Attention for Zero-Shot 3D Anomaly Detection APRIL-GAN: A Zero-/Few-Shot Anomaly Classification and Segmentation Method for CVPR 2023 VAND Workshop Challenge Tracks 1&2: 1st Place on Zero-shot AD and 4th Place on Few-shot AD

Reference 13

Resolution: metadata mismatch; arxiv_id, observed 2026-07-04T19:50:10.588711Z

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Observation acbed739-ee5a-4309-bf40-38e3517b6a26 · inbound

Robust Zero-shot Anomaly Detection under Limited Auxiliary Anomaly Priors cites this paper.

Robust Zero-shot Anomaly Detection under Limited Auxiliary Anomaly Priors APRIL-GAN: A Zero-/Few-Shot Anomaly Classification and Segmentation Method for CVPR 2023 VAND Workshop Challenge Tracks 1&2: 1st Place on Zero-shot AD and 4th Place on Few-shot AD

Reference 8

Resolution: metadata mismatch; arxiv_id, observed 2026-06-30T07:54:21.689631Z

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No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation fae29886-c6e5-4874-9b87-452bf3eb5b8c · inbound

GenAU: Language-Grounded Industrial Anomaly Understanding with Vision-Language Models cites this paper.

GenAU: Language-Grounded Industrial Anomaly Understanding with Vision-Language Models APRIL-GAN: A Zero-/Few-Shot Anomaly Classification and Segmentation Method for CVPR 2023 VAND Workshop Challenge Tracks 1&2: 1st Place on Zero-shot AD and 4th Place on Few-shot AD

Reference 6

Resolution: verified exact; arxiv_id, observed 2026-07-02T13:56:59.033249Z

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No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 4e2e608f-9cac-4287-802b-e00863e65b8f · inbound

LiZAD: A Lightweight Zero-Shot Anomaly Detection Framework for Industrial Manufacturing cites this paper.

LiZAD: A Lightweight Zero-Shot Anomaly Detection Framework for Industrial Manufacturing APRIL-GAN: A Zero-/Few-Shot Anomaly Classification and Segmentation Method for CVPR 2023 VAND Workshop Challenge Tracks 1&2: 1st Place on Zero-shot AD and 4th Place on Few-shot AD

Reference 28

Resolution: verified exact; arxiv_id, observed 2026-07-03T15:58:37.558979Z

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No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.