Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
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 20 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 42 inbound Pith citation observations for arXiv:2305.17382.
A citation records a reference. It does not transfer a finding from one paper to another.
Coverage vector
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-20T06:33:59.587034+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-16T12:28:02.813811Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-07-04T19:50:10.587152Z
Reference resolution
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External citation measurements
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Outbound references
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Pith citing papers
Observation 23bd0412-b700-4983-b79b-3374611bcc92 · inbound
Exploring Zero-Shot Anomaly Detection with CLIP in Medical Imaging: Are We There Yet? cites this paper.
Exploring Zero-Shot Anomaly Detection with CLIP in Medical Imaging: Are We There Yet? 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
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- unresolved
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation d63eacbf-e21b-4496-beaf-c2101d4dc625 · inbound
UniVAD: A Training-free Unified Model for Few-shot Visual Anomaly Detection cites this paper.
UniVAD: A Training-free Unified Model for Few-shot Visual 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 8
- Resolution
- unresolved
- no resolver link, observed 2026-08-11T22:33:28.382641Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation b4f9c1bd-e776-42e6-924b-fb532764f4f0 · inbound
LogicAD: Explainable Anomaly Detection via VLM-based Text Feature Extraction cites this paper.
LogicAD: Explainable Anomaly Detection via VLM-based Text Feature Extraction 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
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 97cea038-f983-41e7-940d-3aa97d0d81fb · inbound
One-to-Normal: Anomaly Personalization for Few-shot Anomaly Detection cites this paper.
One-to-Normal: Anomaly Personalization for 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 5
- Resolution
- unresolved
- no resolver link, observed 2026-08-09T16:18:12.591219Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 0076a537-f097-4ecd-82a4-cead430af7ba · inbound
Multimodal Task Representation Memory Bank vs. Catastrophic Forgetting in Anomaly Detection cites this paper.
Multimodal Task Representation Memory Bank vs. Catastrophic Forgetting in 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 23
- Resolution
- unresolved
- no resolver link, observed 2026-08-08T16:32:09.981435Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation c9006be1-83a2-4810-8f1e-b1466803daa6 · inbound
LAD-Reasoner: Tiny Multimodal Models are Good Reasoners for Logical Anomaly Detection cites this paper.
LAD-Reasoner: Tiny Multimodal Models are Good Reasoners for Logical 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
- unresolved
- no resolver link, observed 2026-08-16T12:28:02.813811Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 354d3d3f-9c99-40ed-931e-314d5f0fe000 · inbound
Real-IAD D3: A Real-World 2D/Pseudo-3D/3D Dataset for Industrial Anomaly Detection cites this paper.
Real-IAD D3: A Real-World 2D/Pseudo-3D/3D Dataset for 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 8
- Resolution
- unresolved
- no resolver link, observed 2026-08-16T11:57:04.563584Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 34cf2953-05b5-4ff7-af31-51ab37f6665e · inbound
LR-IAD:Mask-Free Industrial Anomaly Detection with Logical Reasoning cites this paper.
LR-IAD:Mask-Free Industrial Anomaly Detection with Logical Reasoning 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 2026-08-16T05:54:46.768232Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
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
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
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
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
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
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
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
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation ce6db65b-3081-4f54-a30d-a92532aa6869 · inbound
UltraAD: Fine-Grained Ultrasound Anomaly Classification via Few-Shot CLIP Adaptation cites this paper.
UltraAD: Fine-Grained Ultrasound Anomaly Classification via Few-Shot 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 7
- Resolution
- unresolved
- no resolver link, observed 2026-08-15T18:31:57.027850Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
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
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
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
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
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
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
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
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
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
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
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
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
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
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
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
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
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
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
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
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 1d753d74-8c44-43c9-b695-e9819a10745e · inbound
MCL-AD: Multimodal Collaboration Learning for Zero-Shot 3D Anomaly Detection cites this paper.
MCL-AD: Multimodal Collaboration Learning 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 41
- Resolution
- unresolved
- no resolver link, observed 2026-08-15T15:59:52.627287Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
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
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
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
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
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
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+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
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
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
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
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
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
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
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation fbeb85a0-ea34-49c8-8204-5f5384ca5f29 · inbound
Hyper-FSAD: Training-Free and Language-Free Few-Shot Anomaly Detection via Sparse Hyper Matching cites this paper.
Hyper-FSAD: Training-Free and Language-Free Few-Shot Anomaly Detection via Sparse Hyper Matching 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
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
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 2026-08-20T06:33:59.587034+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
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
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
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+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
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+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
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
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
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+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
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+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
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation b7c5dfe9-d5fe-4bdc-9998-0bae73c06a7d · inbound
FreqAnchorAD: Language-Free Zero-Shot Anomaly Detection via Frequency-Deviation Anchoring cites this paper.
FreqAnchorAD: Language-Free Zero-Shot Anomaly Detection via Frequency-Deviation Anchoring 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
- unresolved
- no resolver link, observed 2026-08-15T15:22:22.420672Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation b33195d7-18d3-4c1a-b6a3-bd3c1b2ac6de · inbound
Dual Anchors, Do It Better: Hierarchical Group Merging for Zero-Shot Anomaly Detection cites this paper.
Dual Anchors, Do It Better: Hierarchical Group Merging 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 7
- Resolution
- unresolved
- no resolver link, observed 2026-08-16T00:27:37.395227Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.