Pith. sign in

Paper Citation Record · LEDGER

LanePerf: a Performance Estimation Framework for Lane Detection

As of 17 August 2026, this Paper Citation Record lists 31 of 31 outbound references and 0 inbound Pith citation observations for arXiv:2507.12894.

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

pith.paper-citation-record.v1
2507.12894 v1

Coverage vector

measured 31 of 31 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-06T16:40:11.336631Z

measured 31 of 31 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-17T06:30:58.91139+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

31 of 31 outbound references displayed

  • verified exact0
  • verified fuzzy23
  • unresolved8
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 0c125afa-2b8d-4ae2-963d-534d5180bc4c · outbound

This paper cites LaneNet: Real-Time Lane Detection Networks for Autonomous Driving.

LanePerf: a Performance Estimation Framework for Lane Detection LaneNet: Real-Time Lane Detection Networks for Autonomous Driving

Reference 1

Resolution
unresolved
no resolver link, observed 2026-08-06T16:40:08.432749Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T16:40:08.432749Z digest=sha256:26b084e2a78ecdc9cb22a18f779e1fd5eb7f289e0a385fd9ac8e84d6e75c33f3

Observation 676acb13-a5a3-47a2-9962-dacb225f34e3 · outbound

This paper cites Spatial as deep: Spatial cnn for traffic scene understanding,.

LanePerf: a Performance Estimation Framework for Lane Detection Spatial as deep: Spatial cnn for traffic scene understanding,

Reference 2

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T16:40:16.731874Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-06T16:40:08.524575Z digest=sha256:f9ebe2030d929c4ab0ff7433c8ceb6696a01b614b42b5b076a6b5a58bd453d23

Observation 922abada-96c0-4d25-8b90-5bcb130a6b91 · outbound

This paper cites Line-cnn: End-to-end traffic line detection with line proposal unit,.

LanePerf: a Performance Estimation Framework for Lane Detection Line-cnn: End-to-end traffic line detection with line proposal unit,

Reference 3

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T16:40:16.410750Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-06T16:40:08.699702Z digest=sha256:005b3d06310e32fd97858f2e2ab83e676a20401b89f2aec6792b1b0c04ed54ce

Observation c28b6612-9b6c-4ac3-841d-04141f5b0162 · outbound

This paper cites Keep your eyes on the lane: Real-time attention- guided lane detection,.

LanePerf: a Performance Estimation Framework for Lane Detection Keep your eyes on the lane: Real-time attention- guided lane detection,

Reference 4

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T16:40:16.135415Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-06T16:40:08.843733Z digest=sha256:33cef263d01b7f950bc7bc5d9b86eca20c1306f356b08b81b96c4546b3dda6b9

Observation 1c8e6060-2d3e-44e2-a936-36df185336ee · outbound

This paper cites Polylanenet: Lane estimation via deep polynomial regression,.

LanePerf: a Performance Estimation Framework for Lane Detection Polylanenet: Lane estimation via deep polynomial regression,

Reference 5

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T16:40:15.979039Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-06T16:40:08.946820Z digest=sha256:a6db970e46236ee3f5ecc0c1f10e4bf721f53834c651027cd5f6bb0bcdca5534

Observation 3223a500-4cf8-488e-832e-ee075d1f1d6b · outbound

This paper cites Clrnet: Cross layer refinement network for lane detection,.

LanePerf: a Performance Estimation Framework for Lane Detection Clrnet: Cross layer refinement network for lane detection,

Reference 6

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T16:40:15.790064Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-06T16:40:09.056974Z digest=sha256:57c6d3134ffa006e4c022fb691411aa8e9957bb30cdef3537441a00a8cd6bfed

Observation 70f239b3-d9ba-4ad4-8e8f-3d0c2fda98e9 · outbound

This paper cites Qui ˜nonero-Candela, M.

LanePerf: a Performance Estimation Framework for Lane Detection Qui ˜nonero-Candela, M

Reference 7

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T16:40:15.622704Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-06T16:40:09.202776Z digest=sha256:18c7d41dfed46805a006803a1b128b5cee9d20e47381723c722cb7d0bdcac939

Observation 1700f9f6-8d0b-435e-a182-855feca84995 · outbound

This paper cites Are labels always necessary for classifier accuracy evaluation?.

LanePerf: a Performance Estimation Framework for Lane Detection Are labels always necessary for classifier accuracy evaluation?

Reference 8

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T16:40:15.442535Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-06T16:40:09.269268Z digest=sha256:05022e84d57f1ff85a8023480e862db36d238ff6b7456b57b1ab436ca68232ca

Observation b915bbab-83d8-4ca3-9d5b-51d6414df5e9 · outbound

This paper cites A Baseline for Detecting Misclassified and Out-of-Distribution Examples in Neural Networks.

LanePerf: a Performance Estimation Framework for Lane Detection A Baseline for Detecting Misclassified and Out-of-Distribution Examples in Neural Networks

Reference 9

Resolution
unresolved
no resolver link, observed 2026-08-06T16:40:09.373813Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T16:40:09.373813Z digest=sha256:780e87f539a4114a844316c24543da1efccbb802b624179a346204143dfa12aa

Observation e580284f-52b6-48d4-bd89-baae983cb2cd · outbound

This paper cites Leveraging Unlabeled Data to Predict Out-of-Distribution Performance.

LanePerf: a Performance Estimation Framework for Lane Detection Leveraging Unlabeled Data to Predict Out-of-Distribution Performance

Reference 10

Resolution
unresolved
no resolver link, observed 2026-08-06T16:40:09.520773Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T16:40:09.520773Z digest=sha256:6199a718683cfac153c7bad5a3b5959d14dfcc4524dd2131a2f863da7ebc4911

Observation 8a98e50e-95c1-4a4b-ad0f-e2279e5a5577 · outbound

This paper cites Predicting with confidence on unseen distributions,.

LanePerf: a Performance Estimation Framework for Lane Detection Predicting with confidence on unseen distributions,

Reference 11

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T16:40:15.257550Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-06T16:40:09.610251Z digest=sha256:73980088c4789c3167bae22389b8455ac38535eff9998905eb7701d856a4511c

Observation a062f6ac-6674-46ef-af63-335e74bbf710 · outbound

This paper cites A simple unified framework for detecting out-of-distribution samples and adversarial attacks,.

LanePerf: a Performance Estimation Framework for Lane Detection A simple unified framework for detecting out-of-distribution samples and adversarial attacks,

Reference 12

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T16:40:15.086274Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-06T16:40:09.702136Z digest=sha256:584fc1e3c73084a8768ffcb7af35200272c3e4d3b60a914eba0bc5efaee67644

Observation 32179134-3581-4610-88ff-342aa4d8db37 · outbound

This paper cites Out-of-distribution detection with deep nearest neighbors,.

LanePerf: a Performance Estimation Framework for Lane Detection Out-of-distribution detection with deep nearest neighbors,

Reference 13

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T16:40:14.915099Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-06T16:40:09.704592Z digest=sha256:134baaf48522e686b7b74496a6cf8421ca5ceb78c9037f85a2475eb8779d6e9e

Observation 9a375125-3053-455c-8e05-b9b9ac2a9c15 · outbound

This paper cites Energy-based out-of- distribution detection,.

LanePerf: a Performance Estimation Framework for Lane Detection Energy-based out-of- distribution detection,

Reference 14

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T16:40:14.742020Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-06T16:40:09.707625Z digest=sha256:95ea8613784cf168815eac8117aa6436298c1e4f76331f52da84d5c47f2d0da9

Observation 1e261686-f466-4a90-af38-a137687c7f5e · outbound

This paper cites Your classifier is secretly an energy based model and you should treat it like one,.

LanePerf: a Performance Estimation Framework for Lane Detection Your classifier is secretly an energy based model and you should treat it like one,

Reference 15

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T16:40:14.506738Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-06T16:40:09.710124Z digest=sha256:ba7a4890ce602285076cc594f1c92a29173bbd79c1b0d173d62525d7029713ab

Observation ade0862b-ee40-41f8-b6d5-e1b46cc9ac17 · outbound

This paper cites Monocular Lane Detection Based on Deep Learning: A Survey.

LanePerf: a Performance Estimation Framework for Lane Detection Monocular Lane Detection Based on Deep Learning: A Survey

Reference 16

Resolution
unresolved
no resolver link, observed 2026-08-06T16:40:09.712872Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T16:40:09.712872Z digest=sha256:e7c196bb0af97954458c4be89ae23e2f17a9b2fb91853eb118a6713a31123bf4

Observation f970d59a-0160-4ecd-bee1-e526ce52fb6a · outbound

This paper cites Lane detection for autonomous driving: Com- prehensive reviews, current challenges, and future predictions,.

LanePerf: a Performance Estimation Framework for Lane Detection Lane detection for autonomous driving: Com- prehensive reviews, current challenges, and future predictions,

Reference 17

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T16:40:14.304873Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-06T16:40:09.749387Z digest=sha256:c3c7fa0e7f6653637831c6af4d25b3f6c54c18c4e26602d3fc14bd89664756e4

Observation bd749660-ee37-4480-9d9b-3ba5add31a01 · outbound

This paper cites Unsupervised labeled lane markers using maps,.

LanePerf: a Performance Estimation Framework for Lane Detection Unsupervised labeled lane markers using maps,

Reference 18

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T16:40:14.008020Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-06T16:40:09.853654Z digest=sha256:1a76c94c111d183ea10beb76d45e76ffed49e850e7353a59d19dc63cf120d739

Observation b75cd171-a89d-44b8-9ab2-5301f7d97099 · outbound

This paper cites Tusimple benchmark,.

LanePerf: a Performance Estimation Framework for Lane Detection Tusimple benchmark,

Reference 19

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T16:40:13.651502Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-06T16:40:09.928375Z digest=sha256:a41d29e4f25d61297343074afe6f3787ab1299c8aafeb428acef68abc22ddba1

Observation 5c71fe07-8dcf-4530-9668-e77ff3844dde · outbound

This paper cites Bridging the gap of lane detection performance between different datasets: Unified viewpoint transformation,.

LanePerf: a Performance Estimation Framework for Lane Detection Bridging the gap of lane detection performance between different datasets: Unified viewpoint transformation,

Reference 20

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T16:40:13.350321Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-06T16:40:10.041352Z digest=sha256:88da60908a1bdcaef1d15884fd0fcdf44a2c76322f9009d8e3f280c744fe49b5

Observation f1871200-329f-4efa-b24f-b7a52ea82489 · outbound

This paper cites Towards weakly-supervised domain adaptation for lane detection,.

LanePerf: a Performance Estimation Framework for Lane Detection Towards weakly-supervised domain adaptation for lane detection,

Reference 21

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T16:40:13.055868Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-06T16:40:10.228699Z digest=sha256:fb4f54c55d58d5e1042df6493b0e74cb937c9991344f00e3669c7e8f7acd3c64

Observation 9a6afff7-2df3-4366-9157-5209682b3d83 · outbound

This paper cites On calibration of modern neural networks,.

LanePerf: a Performance Estimation Framework for Lane Detection On calibration of modern neural networks,

Reference 22

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T16:40:12.826071Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-06T16:40:10.371235Z digest=sha256:d422d969f43e987082119189e427c9133a6a9e2180c0ccc6cf8cd4ed8df673c1

Observation b937c76a-a4dd-4e69-8353-c215e2408f78 · outbound

This paper cites Agreement- on-the-line: Predicting the performance of neural networks under dis- tribution shift,.

LanePerf: a Performance Estimation Framework for Lane Detection Agreement- on-the-line: Predicting the performance of neural networks under dis- tribution shift,

Reference 23

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T16:40:12.505210Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-06T16:40:10.500032Z digest=sha256:7bdc9adad995bce350a749781394d78f79cb0105a1ac28afe84e81b6dca67bb6

Observation c8640350-1ed9-4d9d-a491-455fa01c4de0 · outbound

This paper cites Performance prediction for semantic segmentation by a self-supervised image reconstruction decoder,.

LanePerf: a Performance Estimation Framework for Lane Detection Performance prediction for semantic segmentation by a self-supervised image reconstruction decoder,

Reference 24

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T16:40:12.322530Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-06T16:40:10.592823Z digest=sha256:01e9cafba498993cd26f32d987a00b6779fa8b5c860e7d39f253a7f51217c57a

Observation 4161537d-c236-4aea-aab8-eb752e6f084e · outbound

This paper cites Improving online performance prediction for semantic segmentation,.

LanePerf: a Performance Estimation Framework for Lane Detection Improving online performance prediction for semantic segmentation,

Reference 25

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T16:40:12.165351Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-06T16:40:10.688809Z digest=sha256:29c6ad4e79419e473cbe25d25e9715cc40612306ca8bd269792616b0f8a59307

Observation 05e35157-31cb-4dc0-b145-2c94e87d834b · outbound

This paper cites Deep sets,.

LanePerf: a Performance Estimation Framework for Lane Detection Deep sets,

Reference 26

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T16:40:11.866398Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-06T16:40:10.813933Z digest=sha256:d046b283c355191f32ba786ca7d64d96b1a750d41c20442f743384e5aab0d241

Observation 40d687c3-8b59-4b63-8240-7764a7938c04 · outbound

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

LanePerf: a Performance Estimation Framework for Lane Detection Learning transferable visual models from natural language supervision,

Reference 27

Resolution
unresolved
no resolver link, observed 2026-08-06T16:40:10.939357Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T16:40:10.939357Z digest=sha256:d905a4e666b99618006160ed174c07664c5b1786d7d2de65952ff234042a0d0e

Observation 81f56d2c-6927-499f-b90c-b1643f3bce03 · outbound

This paper cites Imagenet: A large-scale hierarchical image database,.

LanePerf: a Performance Estimation Framework for Lane Detection Imagenet: A large-scale hierarchical image database,

Reference 28

Resolution
unresolved
no resolver link, observed 2026-08-06T16:40:11.028751Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T16:40:11.028751Z digest=sha256:747a39055e91c16f753b57c2b99ae49c42d274acf45765650d69b37bba33caba

Observation 09bb6b60-aa48-48a3-b88f-c7d950089566 · outbound

This paper cites Persformer: 3d lane detection via perspective transformer and the openlane benchmark,.

LanePerf: a Performance Estimation Framework for Lane Detection Persformer: 3d lane detection via perspective transformer and the openlane benchmark,

Reference 29

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T16:40:11.660042Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-06T16:40:11.116032Z digest=sha256:886d5bed1baa3114e80b262b025d80b655f4a32e8e3da6b76b67745bc8c2ddd8

Observation e032052c-860e-4513-9db5-f7d8f9b613d8 · outbound

This paper cites An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale.

LanePerf: a Performance Estimation Framework for Lane Detection An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale

Reference 30

Resolution
unresolved
no resolver link, observed 2026-08-06T16:40:11.225608Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T16:40:11.225608Z digest=sha256:ba858216d50b1750f02ddec9a43b4a6ce4f09759814d70eebf0bd87afa39d28e

Observation 7a305189-0d2b-4236-a0a9-002611f22657 · outbound

This paper cites DINOv2: Learning Robust Visual Features without Supervision.

LanePerf: a Performance Estimation Framework for Lane Detection DINOv2: Learning Robust Visual Features without Supervision

Reference 31

Resolution
unresolved
no resolver link, observed 2026-08-06T16:40:11.336631Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T16:40:11.336631Z digest=sha256:03a4558e90b5e61ea629e1736cbe9252bbca60efd218934c284d24dc3e6257c1

Pith citing papers

No inbound Pith citation observations are available.