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Paper Citation Record · LEDGER

Teacher Supervises Students How to Learn From Partially Labeled Images for Facial Landmark Detection

As of 16 August 2026, this Paper Citation Record lists 47 of 47 outbound references and 0 inbound Pith citation observations for arXiv:1908.02116.

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

pith.paper-citation-record.v1
1908.02116 v3

Coverage vector

measured 47 of 47 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-14T14:57:42.130307Z

measured 47 of 47 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-15T06:32:42.880941+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: cited_works

Reference resolution

47 of 47 outbound references displayed

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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 5cec4f7a-544a-45c1-8e6e-9c3450c01456 · outbound

This paper cites Learning with pseudo-ensembles.

Teacher Supervises Students How to Learn From Partially Labeled Images for Facial Landmark Detection Learning with pseudo-ensembles

Reference 1

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Observation 6645c95b-e9a8-453d-9871-742c22d0edf5 · outbound

This paper cites Curriculum learning.

Teacher Supervises Students How to Learn From Partially Labeled Images for Facial Landmark Detection Curriculum learning

Reference 2

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Observation 49b317b7-014d-4586-a5b7-5ddef7c346dc · outbound

This paper cites Face recognition based on fitting a 3d morphable model.

Teacher Supervises Students How to Learn From Partially Labeled Images for Facial Landmark Detection Face recognition based on fitting a 3d morphable model

Reference 3

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Observation 3a5a8413-f467-43e0-8a2a-c2ba2022cab3 · outbound

This paper cites Combining labeled and un- labeled data with co-training.

Teacher Supervises Students How to Learn From Partially Labeled Images for Facial Landmark Detection Combining labeled and un- labeled data with co-training

Reference 4

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

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Observation 23fc7356-02ec-444e-88c2-45d1d5b07c7c · outbound

This paper cites Convolutional aggregation of local evidence for large pose face alignment.

Teacher Supervises Students How to Learn From Partially Labeled Images for Facial Landmark Detection Convolutional aggregation of local evidence for large pose face alignment

Reference 5

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Observation e7a6a593-8659-4008-8459-3ee4a47d0fca · outbound

This paper cites How far are we from solving the 2D & 3D face alignment problem? (and a dataset of 230,000 3D facial landmarks).

Teacher Supervises Students How to Learn From Partially Labeled Images for Facial Landmark Detection How far are we from solving the 2D & 3D face alignment problem? (and a dataset of 230,000 3D facial landmarks)

Reference 6

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Source-reported events for the cited work

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Observation 530290b7-92ee-470b-bf20-f8e69e80cbba · outbound

This paper cites Face alignment by explicit shape regression.

Teacher Supervises Students How to Learn From Partially Labeled Images for Facial Landmark Detection Face alignment by explicit shape regression

Reference 7

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

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Observation 6c2ca172-6c2a-4f44-bf71-7c8ccfcbe3c7 · outbound

This paper cites Semi-supervised learning.

Teacher Supervises Students How to Learn From Partially Labeled Images for Facial Landmark Detection Semi-supervised learning

Reference 8

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

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Observation 89465c7e-2c79-4426-a691-73a26b618aa2 · outbound

This paper cites Style aggregated network for facial landmark detection.

Teacher Supervises Students How to Learn From Partially Labeled Images for Facial Landmark Detection Style aggregated network for facial landmark detection

Reference 9

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

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Observation df8a53b3-73ae-42a8-9898-169164a5d98d · outbound

This paper cites Network Pruning via Transformable Architecture Search.

Teacher Supervises Students How to Learn From Partially Labeled Images for Facial Landmark Detection Network Pruning via Transformable Architecture Search

Reference 10

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No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

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Observation e91398a0-f3d0-4bd6-bdd7-63c2ec3512af · outbound

This paper cites Supervision-by-Registration: An unsupervised approach to improve the precision of facial landmark detectors.

Teacher Supervises Students How to Learn From Partially Labeled Images for Facial Landmark Detection Supervision-by-Registration: An unsupervised approach to improve the precision of facial landmark detectors

Reference 11

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

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Observation b0ed31b2-8837-47cb-8c48-e16867c92088 · outbound

This paper cites Few-example object detection with model communi- cation.

Teacher Supervises Students How to Learn From Partially Labeled Images for Facial Landmark Detection Few-example object detection with model communi- cation

Reference 12

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Source-reported events for the cited work

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Observation 86c1bf53-e29d-4430-a613-132accef7f21 · outbound

This paper cites Learning to teach.

Teacher Supervises Students How to Learn From Partially Labeled Images for Facial Landmark Detection Learning to teach

Reference 13

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Source-reported events for the cited work

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Observation cced2add-c853-4c9a-aec2-d898141fc3f6 · outbound

This paper cites Generative adversarial nets.

Teacher Supervises Students How to Learn From Partially Labeled Images for Facial Landmark Detection Generative adversarial nets

Reference 14

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Source-reported events for the cited work

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Observation 3719f9b5-a2a2-4470-8384-a51ee2443254 · outbound

This paper cites Distilling the knowledge in a neural network.

Teacher Supervises Students How to Learn From Partially Labeled Images for Facial Landmark Detection Distilling the knowledge in a neural network

Reference 15

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Source-reported events for the cited work

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Observation 831861d4-0d07-43ee-8047-af8fdf5663d0 · outbound

This paper cites Improving landmark localization with semi-supervised learning.

Teacher Supervises Students How to Learn From Partially Labeled Images for Facial Landmark Detection Improving landmark localization with semi-supervised learning

Reference 16

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

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Observation 6dd373c2-edef-4410-bc0a-53629b841438 · outbound

This paper cites Self-paced curriculum learning.

Teacher Supervises Students How to Learn From Partially Labeled Images for Facial Landmark Detection Self-paced curriculum learning

Reference 17

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Source-reported events for the cited work

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Observation 21286e31-83a5-4dec-8c46-7720b6ed8acf · outbound

This paper cites MentorNet: Learning data-driven curriculum for very deep neural networks on corrupted labels.

Teacher Supervises Students How to Learn From Partially Labeled Images for Facial Landmark Detection MentorNet: Learning data-driven curriculum for very deep neural networks on corrupted labels

Reference 18

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Source-reported events for the cited work

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Observation 5a149deb-a045-47e7-9862-efc93622ca61 · outbound

This paper cites Pose- invariant face alignment with a single cnn.

Teacher Supervises Students How to Learn From Partially Labeled Images for Facial Landmark Detection Pose- invariant face alignment with a single cnn

Reference 19

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Source-reported events for the cited work

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Observation 01559f99-ad5a-4028-9b57-d640575ebc34 · outbound

This paper cites Synergy between face alignment and tracking via discriminative global consensus optimization.

Teacher Supervises Students How to Learn From Partially Labeled Images for Facial Landmark Detection Synergy between face alignment and tracking via discriminative global consensus optimization

Reference 20

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Source-reported events for the cited work

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Observation a2d8dd4e-038f-48fb-8006-be7a1aa19e97 · outbound

This paper cites Annotated facial landmarks in the wild: A large- scale, real-world database for facial landmark localization.

Teacher Supervises Students How to Learn From Partially Labeled Images for Facial Landmark Detection Annotated facial landmarks in the wild: A large- scale, real-world database for facial landmark localization

Reference 21

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Source-reported events for the cited work

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Observation 91e6988e-cd70-4da0-883e-bc3a577ce3f0 · outbound

This paper cites Disentangling 3D pose in a dendritic CNN for unconstrained 2D face alignment.

Teacher Supervises Students How to Learn From Partially Labeled Images for Facial Landmark Detection Disentangling 3D pose in a dendritic CNN for unconstrained 2D face alignment

Reference 22

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verified fuzzy
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Source-reported events for the cited work

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Observation 84b66c9a-8e57-4fa2-b846-4f483073aa9d · outbound

This paper cites Self- paced learning for latent variable models.

Teacher Supervises Students How to Learn From Partially Labeled Images for Facial Landmark Detection Self- paced learning for latent variable models

Reference 23

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Source-reported events for the cited work

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Observation 2d4c3d3e-fcb6-464b-a2cb-1a07de5dc981 · outbound

This paper cites Teacher and student joint learning for compact facial landmark detection network.

Teacher Supervises Students How to Learn From Partially Labeled Images for Facial Landmark Detection Teacher and student joint learning for compact facial landmark detection network

Reference 24

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

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Observation 780328f7-4430-449b-b3d6-bebf5c9d2f3f · outbound

This paper cites Prototype propagation networks (PPN) for weakly-supervised few-shot learning on category graph.

Teacher Supervises Students How to Learn From Partially Labeled Images for Facial Landmark Detection Prototype propagation networks (PPN) for weakly-supervised few-shot learning on category graph

Reference 25

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Source-reported events for the cited work

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Observation 852916df-de69-46db-a53b-9dc96f460528 · outbound

This paper cites Exploring disentangled feature representa- tion beyond face identification.

Teacher Supervises Students How to Learn From Partially Labeled Images for Facial Landmark Detection Exploring disentangled feature representa- tion beyond face identification

Reference 26

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Source-reported events for the cited work

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Observation fe220618-9b1d-4930-b155-50f219762298 · outbound

This paper cites A deep regression architecture with two-stage reinitialization for high performance facial landmark detec- tion.

Teacher Supervises Students How to Learn From Partially Labeled Images for Facial Landmark Detection A deep regression architecture with two-stage reinitialization for high performance facial landmark detec- tion

Reference 27

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verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

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Observation ad29d5e4-8823-44cf-bbc4-47ecfa12eeba · outbound

This paper cites Self-paced co-training.

Teacher Supervises Students How to Learn From Partially Labeled Images for Facial Landmark Detection Self-paced co-training

Reference 28

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

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Observation 2ebe5830-3ce8-4de8-bc8e-635fbe7182bc · outbound

This paper cites Direct shape regression net- works for end-to-end face alignment.

Teacher Supervises Students How to Learn From Partially Labeled Images for Facial Landmark Detection Direct shape regression net- works for end-to-end face alignment

Reference 29

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verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

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Observation 4c5fff3b-3627-4f70-8d58-03ab272dd3cb · outbound

This paper cites Stacked hour- glass networks for human pose estimation.

Teacher Supervises Students How to Learn From Partially Labeled Images for Facial Landmark Detection Stacked hour- glass networks for human pose estimation

Reference 30

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Source-reported events for the cited work

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Observation d2084037-1cb7-4cf6-9a9d-2c3f63dea280 · outbound

This paper cites Data distillation: Towards omni- supervised learning.

Teacher Supervises Students How to Learn From Partially Labeled Images for Facial Landmark Detection Data distillation: Towards omni- supervised learning

Reference 31

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

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Observation 8e66f3ba-2056-4e1a-8fb4-4180a7355ace · outbound

This paper cites Hy- perface: A deep multi-task learning framework for face de- tection, landmark localization, pose estimation, and gender recognition.

Teacher Supervises Students How to Learn From Partially Labeled Images for Facial Landmark Detection Hy- perface: A deep multi-task learning framework for face de- tection, landmark localization, pose estimation, and gender recognition

Reference 32

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

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Observation 430591b8-dfb7-47ee-9cfe-69cc5e603062 · outbound

This paper cites Learning to reweight examples for robust deep learning.

Teacher Supervises Students How to Learn From Partially Labeled Images for Facial Landmark Detection Learning to reweight examples for robust deep learning

Reference 33

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

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Observation 20a0d6ef-b373-46d9-98dc-b2901856ffaf · outbound

This paper cites Face alignment via regressing local binary features.

Teacher Supervises Students How to Learn From Partially Labeled Images for Facial Landmark Detection Face alignment via regressing local binary features

Reference 34

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raw_fallback, observed 2026-08-14T14:57:42.884699Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-14T14:57:41.960322Z digest=sha256:3a0af5137850d75a803ae2a930f4dd1be888397802efba2236b0ebab39159673

Observation ff0fec57-165d-4f23-b039-77f27066f4de · outbound

This paper cites 300 faces in-the-wild challenge: The first facial landmark localization challenge.

Teacher Supervises Students How to Learn From Partially Labeled Images for Facial Landmark Detection 300 faces in-the-wild challenge: The first facial landmark localization challenge

Reference 35

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T14:57:42.841019Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-14T14:57:41.968540Z digest=sha256:1046113e8abffafea7d76ca2664289e85915a8a0186ad354cac7d53dd745592c

Observation 9de6f48f-7633-49ed-a636-2dc4e614f1d5 · outbound

This paper cites The first facial landmark tracking in-the-wild challenge: Benchmark and results.

Teacher Supervises Students How to Learn From Partially Labeled Images for Facial Landmark Detection The first facial landmark tracking in-the-wild challenge: Benchmark and results

Reference 36

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T14:57:42.790221Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-14T14:57:41.978586Z digest=sha256:994e157e8a697878b30ae08ed830bde0288007934b05ba3580bc3305325942d9

Observation e783ae6e-1b0e-4129-ad45-350c4c8b0fbd · outbound

This paper cites Quantized densely connected u-nets for efficient landmark localization.

Teacher Supervises Students How to Learn From Partially Labeled Images for Facial Landmark Detection Quantized densely connected u-nets for efficient landmark localization

Reference 37

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T14:57:42.755869Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-14T14:57:41.989997Z digest=sha256:f18d12dad08145b177347e20088969c12eb152fabb3730d0fec59862ae768981

Observation 86d84028-7f1e-4c0e-9c3d-3ad9bf70cdc4 · outbound

This paper cites Mean teachers are better role models: Weight-averaged consistency targets improve semi-supervised deep learning results.

Teacher Supervises Students How to Learn From Partially Labeled Images for Facial Landmark Detection Mean teachers are better role models: Weight-averaged consistency targets improve semi-supervised deep learning results

Reference 38

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T14:57:42.705911Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-14T14:57:42.005283Z digest=sha256:266239dcb1f2288728b9001aea74ae4ccf6125d2234ec8e9e068433344370432

Observation 7b130d54-cd13-409f-9e44-9285baa16d00 · outbound

This paper cites Face2face: Real-time face capture and reenactment of rgb videos.

Teacher Supervises Students How to Learn From Partially Labeled Images for Facial Landmark Detection Face2face: Real-time face capture and reenactment of rgb videos

Reference 39

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T14:57:42.670836Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-14T14:57:42.017620Z digest=sha256:91307f01fb96050fc5b17f3714094fa6aa1021cb2ce1621afba81b24d9a84de3

Observation 18300535-9ea3-45c8-8454-12ccb0021843 · outbound

This paper cites Mnemonic descent method: A recurrent process applied for end-to-end face alignment.

Teacher Supervises Students How to Learn From Partially Labeled Images for Facial Landmark Detection Mnemonic descent method: A recurrent process applied for end-to-end face alignment

Reference 40

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T14:57:42.622046Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-14T14:57:42.028956Z digest=sha256:1d5a358b31372d3805006ca3d14617c2dc60ff68d25101e6ab2e7c5b3c36c182

Observation 6c9be6ce-a69d-4e9c-85b3-53f86f9f91b9 · outbound

This paper cites Convolutional pose machines.

Teacher Supervises Students How to Learn From Partially Labeled Images for Facial Landmark Detection Convolutional pose machines

Reference 41

Resolution
unresolved
no resolver link, observed 2026-08-14T14:57:42.038054Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-14T14:57:42.038054Z digest=sha256:e48eb1f09e7862d16c69ae8379ab9f3344596c2c13a0384cb822eebb918d0087

Observation abd425c0-5c1a-4c40-af54-765abcfbe022 · outbound

This paper cites Facial landmark detection with tweaked convolutional neural networks.

Teacher Supervises Students How to Learn From Partially Labeled Images for Facial Landmark Detection Facial landmark detection with tweaked convolutional neural networks

Reference 42

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T14:57:42.532898Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-14T14:57:42.050360Z digest=sha256:9d8e8f9604bf9f7d130590bf857fc5917f8306df6bb85ea6cc0f91533a484347

Observation e7600a02-f3b3-4428-90cf-54ee7cbcb36e · outbound

This paper cites Recurrent 3d- 2d dual learning for large-pose facial landmark detection.

Teacher Supervises Students How to Learn From Partially Labeled Images for Facial Landmark Detection Recurrent 3d- 2d dual learning for large-pose facial landmark detection

Reference 43

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T14:57:42.491104Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-14T14:57:42.064466Z digest=sha256:bb7f00db5279c7f4e0a965dea9f064f954e295aece83ffac5e030e3255cdf97f

Observation a476797e-da95-4345-bf03-e12233fa238e · outbound

This paper cites Supervised descent method and its applications to face alignment.

Teacher Supervises Students How to Learn From Partially Labeled Images for Facial Landmark Detection Supervised descent method and its applications to face alignment

Reference 44

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T14:57:42.446523Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-14T14:57:42.082103Z digest=sha256:d63394b17c078d88523cd0699de198f1bce0c6a24e13cc9018da914fd861cfa8

Observation 2ec15b27-a5fa-4cae-bc43-a28e1a2233d0 · outbound

This paper cites AutoLoss: Learning discrete schedules for alternate optimization.

Teacher Supervises Students How to Learn From Partially Labeled Images for Facial Landmark Detection AutoLoss: Learning discrete schedules for alternate optimization

Reference 45

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T14:57:42.385783Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-14T14:57:42.092191Z digest=sha256:32933d6c78dba4d4bd7cb0057c11d3d9553d0abbd18982af492ddf3be8bec0df

Observation b244202f-ae41-4a1e-9464-1f513b1485a1 · outbound

This paper cites Unpaired image-to-image translation using cycle- consistent adversarial networks.

Teacher Supervises Students How to Learn From Partially Labeled Images for Facial Landmark Detection Unpaired image-to-image translation using cycle- consistent adversarial networks

Reference 46

Resolution
unresolved
no resolver link, observed 2026-08-14T14:57:42.103685Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-14T14:57:42.103685Z digest=sha256:c7261cbdb017322ce4d9541ab308a596733ef273807708e5e465889118ddc172

Observation fafec0ad-c853-47a2-b7fb-a7d778f1c9cf · outbound

This paper cites Unconstrained face alignment via cascaded compo- sitional learning.

Teacher Supervises Students How to Learn From Partially Labeled Images for Facial Landmark Detection Unconstrained face alignment via cascaded compo- sitional learning

Reference 47

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T14:57:42.308790Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-14T14:57:42.130307Z digest=sha256:4c4e91fcd54644433fff095b46073300de2ec82849c9022b437c9032015b4283

Pith citing papers

No inbound Pith citation observations are available.