What Can We Learn from Harry Potter? An Exploratory Study of Visual Representation Learning from Atypical Videos | Paper Citation Record

Observation c494610a-58b0-4d31-a7b6-0c80420f89ef · outbound

This paper cites Ubnor- mal: New benchmark for supervised open-set video anomaly detection.

What Can We Learn from Harry Potter? An Exploratory Study of Visual Representation Learning from Atypical Videos Ubnor- mal: New benchmark for supervised open-set video anomaly detection

Reference 1

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Observation 4fccf45d-4b79-4a40-95d8-dd36319a87e3 · outbound

This paper cites Towards open set deep networks.

What Can We Learn from Harry Potter? An Exploratory Study of Visual Representation Learning from Atypical Videos Towards open set deep networks

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T14:02:14.498084Z

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Observation cc1f2ea9-6283-4560-9b31-dfbea8634f0f · outbound

This paper cites Is space-time attention all you need for video understanding? InProceedings of the International Conference on Machine Learning (ICML), July 2021.

What Can We Learn from Harry Potter? An Exploratory Study of Visual Representation Learning from Atypical Videos Is space-time attention all you need for video understanding? InProceedings of the International Conference on Machine Learning (ICML), July 2021

Reference 3

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This paper cites Enlarging instance-specific and class-specific information for open-set action recognition.

What Can We Learn from Harry Potter? An Exploratory Study of Visual Representation Learning from Atypical Videos Enlarging instance-specific and class-specific information for open-set action recognition

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T14:02:14.188134Z

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Observation 3a761539-6bbd-443a-baae-8ed237cb4a19 · outbound

This paper cites Elaborative rehearsal for zero-shot action recognition.

What Can We Learn from Harry Potter? An Exploratory Study of Visual Representation Learning from Atypical Videos Elaborative rehearsal for zero-shot action recognition

Reference 5

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This paper cites Wdiscood: Out-of- distribution detection via whitened linear discriminant analysis.

What Can We Learn from Harry Potter? An Exploratory Study of Visual Representation Learning from Atypical Videos Wdiscood: Out-of- distribution detection via whitened linear discriminant analysis

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T14:02:14.024524Z

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Observation 1c77dc5e-7b2b-4290-8ced-d051ba3fbbdc · outbound

This paper cites Haa500: Human-centric atomic action dataset with curated videos.

What Can We Learn from Harry Potter? An Exploratory Study of Visual Representation Learning from Atypical Videos Haa500: Human-centric atomic action dataset with curated videos

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T14:02:13.940558Z

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Observation 5a4adc85-ee08-4796-916e-c98c8e7905db · outbound

This paper cites Towards unknown-aware learning with virtual outlier synthesis.

What Can We Learn from Harry Potter? An Exploratory Study of Visual Representation Learning from Atypical Videos Towards unknown-aware learning with virtual outlier synthesis

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T14:02:13.644210Z

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Observation b5dffb49-5c8c-4155-b694-976d266a0012 · outbound

This paper cites Oops! predicting unintentional ac- tion in video.

What Can We Learn from Harry Potter? An Exploratory Study of Visual Representation Learning from Atypical Videos Oops! predicting unintentional ac- tion in video

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T14:02:13.343116Z

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Observation 4b29c84f-1298-4166-b031-c841b3872aa5 · outbound

This paper cites NovelCraft: A Dataset for Novelty Detection and Discovery in Open Worlds.

What Can We Learn from Harry Potter? An Exploratory Study of Visual Representation Learning from Atypical Videos NovelCraft: A Dataset for Novelty Detection and Discovery in Open Worlds

Reference 10

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Observation f335c71d-ca77-4eab-8624-febaea0ce827 · outbound

This paper cites Unsupervised Representation Learning by Predicting Image Rotations.

What Can We Learn from Harry Potter? An Exploratory Study of Visual Representation Learning from Atypical Videos Unsupervised Representation Learning by Predicting Image Rotations

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-05T14:02:00.976755Z

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Observation a6b816dc-6ac6-4e48-a175-e2b833a6c4dd · outbound

This paper cites Dense open-set recognition with syn- thetic outliers generated by real nvp.

What Can We Learn from Harry Potter? An Exploratory Study of Visual Representation Learning from Atypical Videos Dense open-set recognition with syn- thetic outliers generated by real nvp

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T14:02:13.105602Z

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Observation 3221c6d5-d2aa-47d4-b4f8-ecda163b8460 · outbound

This paper cites Learning to discover novel visual categories via deep transfer clustering.

What Can We Learn from Harry Potter? An Exploratory Study of Visual Representation Learning from Atypical Videos Learning to discover novel visual categories via deep transfer clustering

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T14:02:12.930902Z

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Observation 1bdba9f6-4930-4281-bcb3-8e5bfe56a1a1 · outbound

This paper cites Automatically discovering and learning new visual categories with rank- ing statistics.

What Can We Learn from Harry Potter? An Exploratory Study of Visual Representation Learning from Atypical Videos Automatically discovering and learning new visual categories with rank- ing statistics

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T14:02:12.767073Z

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Observation 76da8525-94fa-4fce-9c5a-82b214854fe7 · outbound

This paper cites Autonovel: Automatically discovering and learning novel visual cate- gories.IEEE Transactions on Pattern Analysis and Machine Intelligence, 44(10): 6767–6781, 2021.

What Can We Learn from Harry Potter? An Exploratory Study of Visual Representation Learning from Atypical Videos Autonovel: Automatically discovering and learning novel visual cate- gories.IEEE Transactions on Pattern Analysis and Machine Intelligence, 44(10): 6767–6781, 2021

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T14:02:12.611309Z

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Observation f4e04a7b-f4d4-4f3d-a2c1-be977b73d837 · outbound

This paper cites Can spatiotemporal 3d cnns retrace the history of 2d cnns and imagenet? InProceedings of the IEEE conference on Computer Vision and Pattern Recognition, pages 6546–6555, 2018.

What Can We Learn from Harry Potter? An Exploratory Study of Visual Representation Learning from Atypical Videos Can spatiotemporal 3d cnns retrace the history of 2d cnns and imagenet? InProceedings of the IEEE conference on Computer Vision and Pattern Recognition, pages 6546–6555, 2018

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T14:02:12.465106Z

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Observation 2fc44e2b-0ff3-4f97-a762-be465276dca6 · outbound

This paper cites Video owl-vit: Temporally-consistent open-world localization in video.

What Can We Learn from Harry Potter? An Exploratory Study of Visual Representation Learning from Atypical Videos Video owl-vit: Temporally-consistent open-world localization in video

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T14:02:12.268186Z

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Observation dbfb2f24-459b-4e98-935d-61a31caf0d61 · outbound

This paper cites A baseline for detecting misclassified and out- of-distribution examples in neural networks.International Conference on Learning Representations, 2017.

What Can We Learn from Harry Potter? An Exploratory Study of Visual Representation Learning from Atypical Videos A baseline for detecting misclassified and out- of-distribution examples in neural networks.International Conference on Learning Representations, 2017

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T14:02:12.100141Z

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Observation eefb184b-9bcd-49a5-9baa-0fa8f33eea86 · outbound

This paper cites Deep anomaly detection with outlier exposure.International Conference on Learning Representations, 2019.

What Can We Learn from Harry Potter? An Exploratory Study of Visual Representation Learning from Atypical Videos Deep anomaly detection with outlier exposure.International Conference on Learning Representations, 2019

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T14:02:11.936421Z

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Observation 86fe09e9-ec1f-4529-a859-ab67b124e03b · outbound

This paper cites Generalized odin: De- tecting out-of-distribution image without learning from out-of-distribution data.

What Can We Learn from Harry Potter? An Exploratory Study of Visual Representation Learning from Atypical Videos Generalized odin: De- tecting out-of-distribution image without learning from out-of-distribution data

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T14:02:11.790544Z

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Observation cad9770e-b561-4603-8198-34cf301899d0 · outbound

This paper cites The Kinetics Human Action Video Dataset.

What Can We Learn from Harry Potter? An Exploratory Study of Visual Representation Learning from Atypical Videos The Kinetics Human Action Video Dataset

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-05T14:02:02.276463Z

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Observation c5621063-d162-46f4-ba36-664fea4ad350 · outbound

This paper cites Chal- lenges, evaluation and opportunities for open-world learning.Nature Machine Intelli- gence, 6(6):580–588, 2024.

What Can We Learn from Harry Potter? An Exploratory Study of Visual Representation Learning from Atypical Videos Chal- lenges, evaluation and opportunities for open-world learning.Nature Machine Intelli- gence, 6(6):580–588, 2024

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T14:02:11.655563Z

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Observation 8e4b0570-c80e-4a39-a6c1-a4438d3c6fd9 · outbound

This paper cites Opengan: Open-set recognition via open data genera- tion.

What Can We Learn from Harry Potter? An Exploratory Study of Visual Representation Learning from Atypical Videos Opengan: Open-set recognition via open data genera- tion

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Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T14:02:11.515219Z

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This paper cites Human action recognition and prediction: A survey.Interna- tional Journal of Computer Vision, 130(5):1366–1401, 2022.

What Can We Learn from Harry Potter? An Exploratory Study of Visual Representation Learning from Atypical Videos Human action recognition and prediction: A survey.Interna- tional Journal of Computer Vision, 130(5):1366–1401, 2022

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Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T14:02:11.384104Z

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Observation fbd90b24-03dd-4766-b5d8-e0a45039c2de · outbound

This paper cites Hmdb: a large video database for human motion recognition.

What Can We Learn from Harry Potter? An Exploratory Study of Visual Representation Learning from Atypical Videos Hmdb: a large video database for human motion recognition

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Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T14:02:11.220752Z

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Observation ad014836-6e04-471f-862e-4581f5b01974 · outbound

This paper cites Resound: Towards action recognition without representation bias.

What Can We Learn from Harry Potter? An Exploratory Study of Visual Representation Learning from Atypical Videos Resound: Towards action recognition without representation bias

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Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T14:02:11.081851Z

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Observation a0c76e42-ebf0-4991-a94e-cad8cda903de · outbound

This paper cites Resource-rational analysis: Understanding hu- man cognition as the optimal use of limited computational resources.Behavioral and brain sciences, 43:e1, 2020.

What Can We Learn from Harry Potter? An Exploratory Study of Visual Representation Learning from Atypical Videos Resource-rational analysis: Understanding hu- man cognition as the optimal use of limited computational resources.Behavioral and brain sciences, 43:e1, 2020

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Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T14:02:10.916377Z

Source-reported events for the cited work

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Observation 613db08a-00f3-4c9e-b2cd-feed15629500 · outbound

This paper cites Abnormal event detection at 150 fps in matlab.

What Can We Learn from Harry Potter? An Exploratory Study of Visual Representation Learning from Atypical Videos Abnormal event detection at 150 fps in matlab

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Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T14:02:10.763141Z

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Observation 0d46ae1c-2184-4541-86e7-a7acb2973982 · outbound

This paper cites Anomaly de- tection in crowded scenes.

What Can We Learn from Harry Potter? An Exploratory Study of Visual Representation Learning from Atypical Videos Anomaly de- tection in crowded scenes

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Observation 1618ee6f-091a-4d8e-bfd4-0d1ecedda25f · outbound

This paper cites HowTo100M: Learning a Text-Video Embedding by Watch- ing Hundred Million Narrated Video Clips.

What Can We Learn from Harry Potter? An Exploratory Study of Visual Representation Learning from Atypical Videos HowTo100M: Learning a Text-Video Embedding by Watch- ing Hundred Million Narrated Video Clips

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Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T14:02:10.680199Z

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Observation 8af1eb24-6367-4916-be5b-33cfbbe09b3c · outbound

This paper cites Poem: Out-of-distribution detection with pos- terior sampling.

What Can We Learn from Harry Potter? An Exploratory Study of Visual Representation Learning from Atypical Videos Poem: Out-of-distribution detection with pos- terior sampling

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Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T14:02:10.551577Z

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Observation 4ab5466a-f3e6-4ce8-9f66-58b1a945f861 · outbound

This paper cites Mo- ments in time dataset: one million videos for event understanding.IEEE transactions on pattern analysis and machine intelligence, 42(2):502–508, 2019.

What Can We Learn from Harry Potter? An Exploratory Study of Visual Representation Learning from Atypical Videos Mo- ments in time dataset: one million videos for event understanding.IEEE transactions on pattern analysis and machine intelligence, 42(2):502–508, 2019

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Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T14:02:10.381973Z

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Observation 8673dd7b-28cf-4cb7-a980-3e24a9fa7645 · outbound

This paper cites Expanding language-image pretrained models for general video recognition.

What Can We Learn from Harry Potter? An Exploratory Study of Visual Representation Learning from Atypical Videos Expanding language-image pretrained models for general video recognition

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Observation 5965cb6c-c003-492c-b3eb-b552385ce969 · outbound

This paper cites Outlier exposure with confidence control for out-of-distribution detec- tion.Neurocomputing, 441:138–150, 2021.

What Can We Learn from Harry Potter? An Exploratory Study of Visual Representation Learning from Atypical Videos Outlier exposure with confidence control for out-of-distribution detec- tion.Neurocomputing, 441:138–150, 2021

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Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T14:02:10.250264Z

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Observation 43b0e379-fa27-46aa-946b-b97cb0ae7e7f · outbound

This paper cites A survey on vision-based human action recognition.Image and vision computing, 28(6):976–990, 2010.

What Can We Learn from Harry Potter? An Exploratory Study of Visual Representation Learning from Atypical Videos A survey on vision-based human action recognition.Image and vision computing, 28(6):976–990, 2010

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Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T14:02:10.120128Z

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Observation 0c88274e-2914-4fa7-b1ab-7574ef637269 · outbound

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

What Can We Learn from Harry Potter? An Exploratory Study of Visual Representation Learning from Atypical Videos Learning transferable visual models from natural language supervision

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Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T14:02:09.995951Z

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Observation 15d0e835-873b-42e7-88cc-876999ec6855 · outbound

This paper cites Fishr: Invariant gradient variances for out-of-distribution generalization.

What Can We Learn from Harry Potter? An Exploratory Study of Visual Representation Learning from Atypical Videos Fishr: Invariant gradient variances for out-of-distribution generalization

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Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T14:02:09.893998Z

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Observation 2a510c09-25be-41ba-ad56-6e5e07bf51cb · outbound

This paper cites If deep learning is the answer, what is the question?Nature Reviews Neuroscience, 22(1):55–67, 2021.

What Can We Learn from Harry Potter? An Exploratory Study of Visual Representation Learning from Atypical Videos If deep learning is the answer, what is the question?Nature Reviews Neuroscience, 22(1):55–67, 2021

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Observation 7f0b9564-2abd-4f87-ab31-6325e71330ce · outbound

This paper cites Meta- recognition: The theory and practice of recognition score analysis.IEEE transactions on pattern analysis and machine intelligence, 33(8):1689–1695, 2011.

What Can We Learn from Harry Potter? An Exploratory Study of Visual Representation Learning from Atypical Videos Meta- recognition: The theory and practice of recognition score analysis.IEEE transactions on pattern analysis and machine intelligence, 33(8):1689–1695, 2011

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Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T14:02:09.751133Z

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Observation 4d9c788d-165c-433b-af06-00aba146c9e3 · outbound

This paper cites UCF101: A Dataset of 101 Human Actions Classes From Videos in The Wild.

What Can We Learn from Harry Potter? An Exploratory Study of Visual Representation Learning from Atypical Videos UCF101: A Dataset of 101 Human Actions Classes From Videos in The Wild

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Resolution: unresolved; no resolver link, observed 2026-08-05T14:02:04.226399Z

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Observation c700c04d-6bc3-40c1-b525-fbf7175aa152 · outbound

This paper cites Real-world anomaly detection in surveillance videos.

What Can We Learn from Harry Potter? An Exploratory Study of Visual Representation Learning from Atypical Videos Real-world anomaly detection in surveillance videos

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Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T14:02:09.577098Z

Source-reported events for the cited work

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Observation e856d248-1424-47e0-b9f9-f84507e96a64 · outbound

This paper cites Human action recognition from various data modalities: A review.IEEE transactions on pattern analysis and machine intelligence, 45(3):3200–3225, 2022.

What Can We Learn from Harry Potter? An Exploratory Study of Visual Representation Learning from Atypical Videos Human action recognition from various data modalities: A review.IEEE transactions on pattern analysis and machine intelligence, 45(3):3200–3225, 2022

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Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T14:02:09.378542Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation e71b4814-8007-4ffb-a313-a972afcad7fe · outbound

This paper cites Black, Ivan Laptev, and Cordelia Schmid.

What Can We Learn from Harry Potter? An Exploratory Study of Visual Representation Learning from Atypical Videos Black, Ivan Laptev, and Cordelia Schmid

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Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T14:02:09.193093Z

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Observation 4afc6e3f-d632-420d-babe-95261d84a10e · outbound

This paper cites Open-set recognition: A good closed-set classifier is all you need? 2021.

What Can We Learn from Harry Potter? An Exploratory Study of Visual Representation Learning from Atypical Videos Open-set recognition: A good closed-set classifier is all you need? 2021

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Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T14:02:08.991793Z

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Observation bedd9d56-d3cb-436c-90a5-96bb781ca5fc · outbound

This paper cites Generalized category discovery.

What Can We Learn from Harry Potter? An Exploratory Study of Visual Representation Learning from Atypical Videos Generalized category discovery

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Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T14:02:08.881327Z

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Observation fec39636-34ab-453b-9c37-6666dc260ca5 · outbound

This paper cites No representation rules them all in category discovery.

What Can We Learn from Harry Potter? An Exploratory Study of Visual Representation Learning from Atypical Videos No representation rules them all in category discovery

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Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T14:02:08.640276Z

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Observation 5bac9760-7640-4d5d-8880-f111f096f965 · outbound

This paper cites Self-supervised video representation learning by pace prediction.

What Can We Learn from Harry Potter? An Exploratory Study of Visual Representation Learning from Atypical Videos Self-supervised video representation learning by pace prediction

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Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T14:02:08.480574Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation ac66d5d3-b773-4a9e-b045-3b934958f55b · outbound

This paper cites Action recognition and detection by com- bining motion and appearance features.THUMOS14 Action Recognition Challenge, 1 (2):2, 2014.

What Can We Learn from Harry Potter? An Exploratory Study of Visual Representation Learning from Atypical Videos Action recognition and detection by com- bining motion and appearance features.THUMOS14 Action Recognition Challenge, 1 (2):2, 2014

Reference 48

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T14:02:08.289468Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 3d76a287-af6c-469c-bde0-b99ccc3cfd3f · outbound

This paper cites ActionCLIP: A New Paradigm for Video Action Recognition.

What Can We Learn from Harry Potter? An Exploratory Study of Visual Representation Learning from Atypical Videos ActionCLIP: A New Paradigm for Video Action Recognition

Reference 49

Resolution: unresolved; no resolver link, observed 2026-08-05T14:02:04.935174Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3a16aaa4-b86f-4306-9abd-019f955ab3f0 · outbound

This paper cites Openood: Benchmark- ing generalized out-of-distribution detection.Advances in Neural Information Pro- cessing Systems, 35:32598–32611, 2022.

What Can We Learn from Harry Potter? An Exploratory Study of Visual Representation Learning from Atypical Videos Openood: Benchmark- ing generalized out-of-distribution detection.Advances in Neural Information Pro- cessing Systems, 35:32598–32611, 2022

Reference 50

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T14:02:08.072192Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 5e5073cc-84dd-4569-b06c-64f73cb7855a · outbound

This paper cites Generalized out-of- distribution detection: A survey.International Journal of Computer Vision, pages 1–28, 2024.

What Can We Learn from Harry Potter? An Exploratory Study of Visual Representation Learning from Atypical Videos Generalized out-of- distribution detection: A survey.International Journal of Computer Vision, pages 1–28, 2024

Reference 51

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T14:02:07.865968Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 9b7c7aa8-c1e7-479a-a0ba-930dae3c597b · outbound

This paper cites Un- derstanding deep learning (still) requires rethinking generalization.Communications of the ACM, 64(3):107–115, 2021.

What Can We Learn from Harry Potter? An Exploratory Study of Visual Representation Learning from Atypical Videos Un- derstanding deep learning (still) requires rethinking generalization.Communications of the ACM, 64(3):107–115, 2021

Reference 52

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T14:02:07.645931Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation c095afd6-0bd8-45f0-b4fa-af9e02b90dfe · outbound

This paper cites Mixture outlier exposure: Towards out-of-distribution detection in fine-grained en- vironments.

What Can We Learn from Harry Potter? An Exploratory Study of Visual Representation Learning from Atypical Videos Mixture outlier exposure: Towards out-of-distribution detection in fine-grained en- vironments

Reference 53

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T14:02:07.407597Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 47a6f305-ac19-41bb-9aaf-b037d21b52b0 · outbound

This paper cites Open- mix: Reviving known knowledge for discovering novel visual categories in an open world.

What Can We Learn from Harry Potter? An Exploratory Study of Visual Representation Learning from Atypical Videos Open- mix: Reviving known knowledge for discovering novel visual categories in an open world

Reference 54

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T14:02:07.199110Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation c24e56f8-18e8-42a7-9e9e-934521c96303 · outbound

This paper cites Learning placeholders for open-set recognition.

What Can We Learn from Harry Potter? An Exploratory Study of Visual Representation Learning from Atypical Videos Learning placeholders for open-set recognition

Reference 55

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T14:02:07.062700Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation aac02e99-d669-4272-bca6-ee4f99b20c7c · outbound

This paper cites Diversified outlier exposure for out-of-distribution detection via in- formative extrapolation.Advances in Neural Information Processing Systems, 36: 22702–22734, 2023.

What Can We Learn from Harry Potter? An Exploratory Study of Visual Representation Learning from Atypical Videos Diversified outlier exposure for out-of-distribution detection via in- formative extrapolation.Advances in Neural Information Processing Systems, 36: 22702–22734, 2023

Reference 56

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T14:02:06.914683Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 3c238e71-90f7-44f6-bf6e-4e3031c6bbd7 · outbound

This paper cites Unleashing mask: Explore the intrinsic out-of-distribution detection capa- bility.

What Can We Learn from Harry Potter? An Exploratory Study of Visual Representation Learning from Atypical Videos Unleashing mask: Explore the intrinsic out-of-distribution detection capa- bility

Reference 57

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T14:02:06.803921Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 33fcc031-32cb-4f0a-afcd-e5f7ede42976 · outbound

This paper cites Towards universal representation for unseen action recognition.

What Can We Learn from Harry Potter? An Exploratory Study of Visual Representation Learning from Atypical Videos Towards universal representation for unseen action recognition

Reference 58

Resolution: unresolved; no resolver link, observed 2026-08-05T14:02:05.763997Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2722e854-314d-452b-90d6-c81958eb97ce · outbound

This paper cites Towards open set video anomaly detec- tion.

What Can We Learn from Harry Potter? An Exploratory Study of Visual Representation Learning from Atypical Videos Towards open set video anomaly detec- tion

Reference 59

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T14:02:06.642411Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Coverage vector

Reference resolution

Outbound references

Pith citing papers