Adapt, But Don't Forget: Fine-Tuning and Contrastive Routing for Lane Detection under Distribution Shift | Paper Citation Record

Observation 9b5c53f8-0fbf-4e2b-9035-0edf46e24c89 · outbound

This paper cites BSNet: Lane Detection via Draw B-spline Curves Nearby.

Adapt, But Don't Forget: Fine-Tuning and Contrastive Routing for Lane Detection under Distribution Shift BSNet: Lane Detection via Draw B-spline Curves Nearby

Reference 1

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Observation 6dfbe703-5e18-4684-b127-9b58155ba17d · outbound

This paper cites MMDetection: Open MMLab Detection Toolbox and Benchmark.

Adapt, But Don't Forget: Fine-Tuning and Contrastive Routing for Lane Detection under Distribution Shift MMDetection: Open MMLab Detection Toolbox and Benchmark

Reference 2

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Observation bd3fb3a6-0b16-4876-bc29-ce1f831c5e6b · outbound

This paper cites Deeplab: Semantic image segmentation with deep convolutional nets, atrous convolu- tion, and fully connected crfs.

Adapt, But Don't Forget: Fine-Tuning and Contrastive Routing for Lane Detection under Distribution Shift Deeplab: Semantic image segmentation with deep convolutional nets, atrous convolu- tion, and fully connected crfs

Reference 3

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Observation 0a399058-0f25-4e28-89d5-8a4c63a44342 · outbound

This paper cites Rethinking Atrous Convolution for Semantic Image Segmentation.

Adapt, But Don't Forget: Fine-Tuning and Contrastive Routing for Lane Detection under Distribution Shift Rethinking Atrous Convolution for Semantic Image Segmentation

Reference 4

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Observation 0508287b-a874-4b86-9736-71f50cf1ef9a · outbound

This paper cites Do- main adaptation for semantic segmentation with maximum squares loss.

Adapt, But Don't Forget: Fine-Tuning and Contrastive Routing for Lane Detection under Distribution Shift Do- main adaptation for semantic segmentation with maximum squares loss

Reference 5

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Observation 756f43ef-d171-463b-ae47-37043dbf1a2d · outbound

This paper cites A simple framework for contrastive learning of visual representations.

Adapt, But Don't Forget: Fine-Tuning and Contrastive Routing for Lane Detection under Distribution Shift A simple framework for contrastive learning of visual representations

Reference 6

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Observation 62de02c3-ef00-4142-a81b-dd74d0633b61 · outbound

This paper cites Weakly-supervised domain adaptive semantic segmentation with prototypical contrastive learning.

Adapt, But Don't Forget: Fine-Tuning and Contrastive Routing for Lane Detection under Distribution Shift Weakly-supervised domain adaptive semantic segmentation with prototypical contrastive learning

Reference 7

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

Adapt, But Don't Forget: Fine-Tuning and Contrastive Routing for Lane Detection under Distribution Shift An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale

Reference 8

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Observation 865311c8-17eb-4ee0-95ae-dee6786b8a60 · outbound

This paper cites Few- shot object detection with attention-rpn and multi-relation detector.

Adapt, But Don't Forget: Fine-Tuning and Contrastive Routing for Lane Detection under Distribution Shift Few- shot object detection with attention-rpn and multi-relation detector

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:05:20.778229Z

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Observation 662d5069-e4b6-40cc-b313-1f61c0816f48 · outbound

This paper cites Assisttaxi: A comprehensive dataset for taxiway analysis and autonomous operations.

Adapt, But Don't Forget: Fine-Tuning and Contrastive Routing for Lane Detection under Distribution Shift Assisttaxi: A comprehensive dataset for taxiway analysis and autonomous operations

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:05:20.759524Z

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Observation 2ae874ef-a511-421f-b45d-73dfad7a3fa3 · outbound

This paper cites Cross dataset analysis and network architecture repair for autonomous car lane detection.

Adapt, But Don't Forget: Fine-Tuning and Contrastive Routing for Lane Detection under Distribution Shift Cross dataset analysis and network architecture repair for autonomous car lane detection

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:05:20.737877Z

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Observation 0b8614fd-741d-4e13-8988-7b94a0bd190a · outbound

This paper cites Runway vs.

Adapt, But Don't Forget: Fine-Tuning and Contrastive Routing for Lane Detection under Distribution Shift Runway vs

Reference 12

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Observation 8b83e901-ca17-4257-bf4c-4c72718990c6 · outbound

This paper cites Bootstrap your own latent-a new approach to self-supervised learning.

Adapt, But Don't Forget: Fine-Tuning and Contrastive Routing for Lane Detection under Distribution Shift Bootstrap your own latent-a new approach to self-supervised learning

Reference 13

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Observation 5a228690-5428-4ef1-81f7-f0330823377f · outbound

This paper cites Domain adaptation for medical image analysis: a survey.

Adapt, But Don't Forget: Fine-Tuning and Contrastive Routing for Lane Detection under Distribution Shift Domain adaptation for medical image analysis: a survey

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:05:20.671911Z

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Observation a145e810-28a6-44ac-9c85-29dbefd31ed4 · outbound

This paper cites Laneformer: Object- aware row-column transformers for lane detection.

Adapt, But Don't Forget: Fine-Tuning and Contrastive Routing for Lane Detection under Distribution Shift Laneformer: Object- aware row-column transformers for lane detection

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:05:20.648612Z

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Observation b9c6e6a2-23cd-4336-9d8d-2133560e7234 · outbound

This paper cites Expanding low-density latent regions for open-set object detection.

Adapt, But Don't Forget: Fine-Tuning and Contrastive Routing for Lane Detection under Distribution Shift Expanding low-density latent regions for open-set object detection

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:05:20.628188Z

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Observation 8b2dec22-f274-4234-9d36-e904bcf115ea · outbound

This paper cites Deep residual learning for image recognition.

Adapt, But Don't Forget: Fine-Tuning and Contrastive Routing for Lane Detection under Distribution Shift Deep residual learning for image recognition

Reference 17

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Observation 04b1d197-c608-4f7b-b3ee-cda55729f38b · outbound

This paper cites Mask r-cnn.

Adapt, But Don't Forget: Fine-Tuning and Contrastive Routing for Lane Detection under Distribution Shift Mask r-cnn

Reference 18

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Observation b85c3301-f2e8-469e-9381-95b07777f5f0 · outbound

This paper cites Momentum contrast for unsupervised visual rep- resentation learning.

Adapt, But Don't Forget: Fine-Tuning and Contrastive Routing for Lane Detection under Distribution Shift Momentum contrast for unsupervised visual rep- resentation learning

Reference 19

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Observation ff1837bd-2a79-4ed9-88a6-38c8aabeef03 · outbound

This paper cites Clrernet: improving con- fidence of lane detection with laneiou.

Adapt, But Don't Forget: Fine-Tuning and Contrastive Routing for Lane Detection under Distribution Shift Clrernet: improving con- fidence of lane detection with laneiou

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:05:20.572463Z

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Observation 2e5cf9b4-961c-4d6d-8160-d227a98744b8 · outbound

This paper cites Learning lightweight lane detection cnns by self at- tention distillation.

Adapt, But Don't Forget: Fine-Tuning and Contrastive Routing for Lane Detection under Distribution Shift Learning lightweight lane detection cnns by self at- tention distillation

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:05:20.551180Z

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Observation 5e2de345-831c-447b-bcbd-2617ec930600 · outbound

This paper cites Mic: Masked image consistency for context- enhanced domain adaptation.

Adapt, But Don't Forget: Fine-Tuning and Contrastive Routing for Lane Detection under Distribution Shift Mic: Masked image consistency for context- enhanced domain adaptation

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:05:20.532183Z

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Observation f2f09857-c664-4346-a244-9e7ae31037f8 · outbound

This paper cites Sim-to- real domain adaptation for lane detection and classification in autonomous driving.

Adapt, But Don't Forget: Fine-Tuning and Contrastive Routing for Lane Detection under Distribution Shift Sim-to- real domain adaptation for lane detection and classification in autonomous driving

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:05:20.510457Z

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Observation 0e4c73ae-6a9f-4acd-92dc-acc9020ab1d6 · outbound

This paper cites Measuring catastrophic for- getting in neural networks.

Adapt, But Don't Forget: Fine-Tuning and Contrastive Routing for Lane Detection under Distribution Shift Measuring catastrophic for- getting in neural networks

Reference 24

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Observation 1e5f71e5-b1ab-44f2-8212-d715e003feca · outbound

This paper cites Clas- sification of microstructure images of metals using transfer learning.

Adapt, But Don't Forget: Fine-Tuning and Contrastive Routing for Lane Detection under Distribution Shift Clas- sification of microstructure images of metals using transfer learning

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:05:20.459824Z

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Observation 03da887a-4bd1-404a-8cae-c186d162b1d7 · outbound

This paper cites Alina: Advanced line identification and notation algorithm.

Adapt, But Don't Forget: Fine-Tuning and Contrastive Routing for Lane Detection under Distribution Shift Alina: Advanced line identification and notation algorithm

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:05:20.440363Z

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Observation 661115fe-54a5-4f90-948d-0010ba1efbc2 · outbound

This paper cites Detection of cavities from oral images using convolutional neural networks.

Adapt, But Don't Forget: Fine-Tuning and Contrastive Routing for Lane Detection under Distribution Shift Detection of cavities from oral images using convolutional neural networks

Reference 27

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Observation 42585ff9-5978-4e5e-9ac8-7490c71ad75b · outbound

This paper cites Supervised contrastive learning.

Adapt, But Don't Forget: Fine-Tuning and Contrastive Routing for Lane Detection under Distribution Shift Supervised contrastive learning

Reference 28

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Observation a8e960f1-b561-41df-8378-08c008eac793 · outbound

This paper cites Overcoming catastrophic forgetting in neu- ral networks.

Adapt, But Don't Forget: Fine-Tuning and Contrastive Routing for Lane Detection under Distribution Shift Overcoming catastrophic forgetting in neu- ral networks

Reference 29

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Observation f777c119-f2c0-4bb9-9f44-d7d1fde534ac · outbound

This paper cites Key points esti- mation and point instance segmentation approach for lane detection.

Adapt, But Don't Forget: Fine-Tuning and Contrastive Routing for Lane Detection under Distribution Shift Key points esti- mation and point instance segmentation approach for lane detection

Reference 30

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Observation acb43242-2d7f-4b7b-9f32-1516eadc13d6 · outbound

This paper cites Vpgnet: Vanishing point guided network for lane and road marking detection and recognition.

Adapt, But Don't Forget: Fine-Tuning and Contrastive Routing for Lane Detection under Distribution Shift Vpgnet: Vanishing point guided network for lane and road marking detection and recognition

Reference 31

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Observation 6075cbc0-c7d3-44f4-b484-709fba1d34e8 · outbound

This paper cites Multi-level domain adaptation for lane detection.

Adapt, But Don't Forget: Fine-Tuning and Contrastive Routing for Lane Detection under Distribution Shift Multi-level domain adaptation for lane detection

Reference 32

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Observation f6e2262a-d95e-46a7-bc18-1d35175ebcee · outbound

This paper cites Constructing self-motivated pyramid curriculums for cross- domain semantic segmentation: A non-adversarial approach.

Adapt, But Don't Forget: Fine-Tuning and Contrastive Routing for Lane Detection under Distribution Shift Constructing self-motivated pyramid curriculums for cross- domain semantic segmentation: A non-adversarial approach

Reference 33

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Adapt, But Don't Forget: Fine-Tuning and Contrastive Routing for Lane Detection under Distribution Shift Feature pyra- mid networks for object detection

Reference 34

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This paper cites Cond- lanenet: a top-to-down lane detection framework based on conditional convolution.

Adapt, But Don't Forget: Fine-Tuning and Contrastive Routing for Lane Detection under Distribution Shift Cond- lanenet: a top-to-down lane detection framework based on conditional convolution

Reference 35

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Observation 66a443f8-a103-44ff-b3c8-bcea1632f945 · outbound

This paper cites End- to-end lane shape prediction with transformers.

Adapt, But Don't Forget: Fine-Tuning and Contrastive Routing for Lane Detection under Distribution Shift End- to-end lane shape prediction with transformers

Reference 36

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Observation 324cffc3-7b98-463a-89e1-3ff5e3bff529 · outbound

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Adapt, But Don't Forget: Fine-Tuning and Contrastive Routing for Lane Detection under Distribution Shift Fully convolutional networks for semantic segmentation

Reference 37

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Adapt, But Don't Forget: Fine-Tuning and Contrastive Routing for Lane Detection under Distribution Shift Gradient episodic memory for continual learning

Reference 38

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Observation f175fdcd-beb2-4e40-94c3-bc85b8bc6a35 · outbound

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Adapt, But Don't Forget: Fine-Tuning and Contrastive Routing for Lane Detection under Distribution Shift Decoupled Weight Decay Regularization

Reference 39

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This paper cites Weakly-supervised cross- domain road scene segmentation via multi-level curriculum adaptation.

Adapt, But Don't Forget: Fine-Tuning and Contrastive Routing for Lane Detection under Distribution Shift Weakly-supervised cross- domain road scene segmentation via multi-level curriculum adaptation

Reference 40

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This paper cites Understanding the role of train- ing regimes in continual learning.

Adapt, But Don't Forget: Fine-Tuning and Contrastive Routing for Lane Detection under Distribution Shift Understanding the role of train- ing regimes in continual learning

Reference 41

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Observation d9bf2d5b-ee30-440d-a367-2bc69d2349c3 · outbound

This paper cites Lane detection technique based on perspective transformation and histogram analysis for self-driving cars.

Adapt, But Don't Forget: Fine-Tuning and Contrastive Routing for Lane Detection under Distribution Shift Lane detection technique based on perspective transformation and histogram analysis for self-driving cars

Reference 42

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Observation 1b031595-7b85-4ed6-95a5-b7052e142eea · outbound

This paper cites Towards end-to-end lane detection: an instance segmentation approach.

Adapt, But Don't Forget: Fine-Tuning and Contrastive Routing for Lane Detection under Distribution Shift Towards end-to-end lane detection: an instance segmentation approach

Reference 43

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This paper cites Dissecting Catastrophic Forgetting in Continual Learning by Deep Visualization.

Adapt, But Don't Forget: Fine-Tuning and Contrastive Routing for Lane Detection under Distribution Shift Dissecting Catastrophic Forgetting in Continual Learning by Deep Visualization

Reference 44

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Observation cebfae88-d8a4-47e0-908a-2bc529303d2c · outbound

This paper cites Lanecor- rect: Self-supervised lane detection.

Adapt, But Don't Forget: Fine-Tuning and Contrastive Routing for Lane Detection under Distribution Shift Lanecor- rect: Self-supervised lane detection

Reference 45

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Observation 673d2856-b74e-43cb-8c91-07a537482450 · outbound

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

Adapt, But Don't Forget: Fine-Tuning and Contrastive Routing for Lane Detection under Distribution Shift Spatial as deep: Spatial cnn for traffic scene understanding

Reference 46

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:05:19.585443Z

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Observation ce1b5f57-a79e-4f71-90b2-7cfd61fd8e18 · outbound

This paper cites Ultra fast structure- aware deep lane detection.

Adapt, But Don't Forget: Fine-Tuning and Contrastive Routing for Lane Detection under Distribution Shift Ultra fast structure- aware deep lane detection

Reference 47

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Observation 30f91b5c-9870-4a46-b54a-b6452e8b578f · outbound

This paper cites Ultra fast deep lane detection with hybrid anchor driven ordinal classification.

Adapt, But Don't Forget: Fine-Tuning and Contrastive Routing for Lane Detection under Distribution Shift Ultra fast deep lane detection with hybrid anchor driven ordinal classification

Reference 48

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:05:19.333930Z

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Observation b06150a6-b443-417e-bfe2-20d1f366683e · outbound

This paper cites Focus on local: Detecting lane marker from bottom up via key point.

Adapt, But Don't Forget: Fine-Tuning and Contrastive Routing for Lane Detection under Distribution Shift Focus on local: Detecting lane marker from bottom up via key point

Reference 49

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:05:19.193295Z

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Observation 022e953e-d0a1-40c4-abe0-13a0a475966d · outbound

This paper cites Anatomy of Catastrophic Forgetting: Hidden Representations and Task Semantics.

Adapt, But Don't Forget: Fine-Tuning and Contrastive Routing for Lane Detection under Distribution Shift Anatomy of Catastrophic Forgetting: Hidden Representations and Task Semantics

Reference 50

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Observation 0bbc376b-6b59-4ec7-99b8-8c5131987983 · outbound

This paper cites Erfnet: Efficient residual factorized convnet for real-time semantic segmentation.

Adapt, But Don't Forget: Fine-Tuning and Contrastive Routing for Lane Detection under Distribution Shift Erfnet: Efficient residual factorized convnet for real-time semantic segmentation

Reference 51

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:05:18.981370Z

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No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation e59f7291-2865-4cb3-a0ab-ddedf698901f · outbound

This paper cites U- net: Convolutional networks for biomedical image segmen- tation.

Adapt, But Don't Forget: Fine-Tuning and Contrastive Routing for Lane Detection under Distribution Shift U- net: Convolutional networks for biomedical image segmen- tation

Reference 52

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:05:18.822556Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 1fe7a153-4d66-4195-911a-2c46e48ffc14 · outbound

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

Adapt, But Don't Forget: Fine-Tuning and Contrastive Routing for Lane Detection under Distribution Shift Keep your eyes on the lane: Real-time attention-guided lane detection

Reference 53

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:05:18.609605Z

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No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation dfdae7bf-10f5-4874-a56f-85ea12352efa · outbound

This paper cites Polylanenet: Lane estimation via deep polynomial regres- sion.

Adapt, But Don't Forget: Fine-Tuning and Contrastive Routing for Lane Detection under Distribution Shift Polylanenet: Lane estimation via deep polynomial regres- sion

Reference 54

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:05:18.431435Z

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No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 78079af3-351d-43d5-81c3-098ffd59bba3 · outbound

This paper cites Adversarial discriminative domain adaptation.

Adapt, But Don't Forget: Fine-Tuning and Contrastive Routing for Lane Detection under Distribution Shift Adversarial discriminative domain adaptation

Reference 55

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:05:18.308821Z

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No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation a3d41f05-e011-4241-8cb4-5de586dbd8b5 · outbound

This paper cites A keypoint-based global association network for lane detection.

Adapt, But Don't Forget: Fine-Tuning and Contrastive Routing for Lane Detection under Distribution Shift A keypoint-based global association network for lane detection

Reference 56

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:05:18.185121Z

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No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 1ff13315-d3bf-43c7-b480-5a693c1645d7 · outbound

This paper cites Exploring cross-image pixel contrast for semantic segmentation.

Adapt, But Don't Forget: Fine-Tuning and Contrastive Routing for Lane Detection under Distribution Shift Exploring cross-image pixel contrast for semantic segmentation

Reference 57

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:05:17.977517Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 85eac367-6ace-4fca-bc2c-b9ab14986839 · outbound

This paper cites Curvelane-nas: Unifying lane- sensitive architecture search and adaptive point blending.

Adapt, But Don't Forget: Fine-Tuning and Contrastive Routing for Lane Detection under Distribution Shift Curvelane-nas: Unifying lane- sensitive architecture search and adaptive point blending

Reference 58

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:05:17.811622Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 39340f52-b03e-4955-ac89-5f405dbfa442 · outbound

This paper cites Lane detection in autonomous vehicles: A systematic review.

Adapt, But Don't Forget: Fine-Tuning and Contrastive Routing for Lane Detection under Distribution Shift Lane detection in autonomous vehicles: A systematic review

Reference 59

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:05:17.689687Z

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No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 770d88b5-ad98-4958-9409-e8463fd8f921 · outbound

This paper cites Recent advances in transfer learning for cross-dataset visual recognition: A problem-oriented perspective.

Adapt, But Don't Forget: Fine-Tuning and Contrastive Routing for Lane Detection under Distribution Shift Recent advances in transfer learning for cross-dataset visual recognition: A problem-oriented perspective

Reference 60

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:05:17.514176Z

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No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 0cb06032-edef-47af-8087-302c1aa48457 · outbound

This paper cites Resa: Recurrent feature-shift ag- gregator for lane detection.

Adapt, But Don't Forget: Fine-Tuning and Contrastive Routing for Lane Detection under Distribution Shift Resa: Recurrent feature-shift ag- gregator for lane detection

Reference 61

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:05:17.322576Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 9c5143d1-a9d3-43cb-8fdd-94bd6d582848 · outbound

This paper cites Clrnet: Cross layer re- finement network for lane detection.

Adapt, But Don't Forget: Fine-Tuning and Contrastive Routing for Lane Detection under Distribution Shift Clrnet: Cross layer re- finement network for lane detection

Reference 62

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:05:17.168094Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 83fc0487-edef-4cf8-b14e-1ac43501aa05 · outbound

This paper cites Clrnetv2: A faster and stronger lane detector.

Adapt, But Don't Forget: Fine-Tuning and Contrastive Routing for Lane Detection under Distribution Shift Clrnetv2: A faster and stronger lane detector

Reference 63

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:05:17.015009Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 40a469eb-2109-43f8-8df4-51b92e4cbdd2 · outbound

This paper cites To- wards weakly-supervised domain adaptation for lane detec- tion.

Adapt, But Don't Forget: Fine-Tuning and Contrastive Routing for Lane Detection under Distribution Shift To- wards weakly-supervised domain adaptation for lane detec- tion

Reference 64

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:05:16.828018Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation f9e9bc1e-923b-49db-92fb-bdcd1df89ab7 · outbound

This paper cites Unsupervised Domain Adaptive Lane Detection via Contextual Contrast and Aggregation.

Adapt, But Don't Forget: Fine-Tuning and Contrastive Routing for Lane Detection under Distribution Shift Unsupervised Domain Adaptive Lane Detection via Contextual Contrast and Aggregation

Reference 65

Resolution: verified exact; local_arxiv, observed 2026-08-06T15:05:15.672551Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation be3de8a1-8559-4c93-bc5c-88cff2efb314 · outbound

This paper cites Balanced contrastive learn- ing for long-tailed visual recognition.

Adapt, But Don't Forget: Fine-Tuning and Contrastive Routing for Lane Detection under Distribution Shift Balanced contrastive learn- ing for long-tailed visual recognition

Reference 66

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:05:16.652800Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation f49c8a38-8eea-4b89-b5b7-57d80d69d784 · outbound

This paper cites Contrastive learning for lane detection via cross-similarity.

Adapt, But Don't Forget: Fine-Tuning and Contrastive Routing for Lane Detection under Distribution Shift Contrastive learning for lane detection via cross-similarity

Reference 67

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:05:16.514695Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 0c58cee2-b200-4774-bf17-0b82d8e41afe · outbound

This paper cites • Bias: θ′ c = {bias(θi)}, where i ∈ {H} or {N, H}.

Adapt, But Don't Forget: Fine-Tuning and Contrastive Routing for Lane Detection under Distribution Shift • Bias: θ′ c = {bias(θi)}, where i ∈ {H} or {N, H}

Reference 69

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:05:16.204634Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation d3f4d73e-565b-44a7-86e7-69be77630f2e · outbound

This paper cites Each table reports both source (CU- Lane) and target performance after selectively fine-tuning model components.

Adapt, But Don't Forget: Fine-Tuning and Contrastive Routing for Lane Detection under Distribution Shift Each table reports both source (CU- Lane) and target performance after selectively fine-tuning model components

Reference 70

Resolution: malformed identifier; raw_fallback, observed 2026-08-06T15:05:16.061639Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 788f3976-6025-4098-8b06-f232d87fefea · outbound

This paper cites an unresolved cited work.

Adapt, But Don't Forget: Fine-Tuning and Contrastive Routing for Lane Detection under Distribution Shift Unresolved cited work

Reference 2024

Resolution: unresolved; raw_fallback, observed 2026-08-06T15:05:16.325347Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

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