Spatial Lifting for Dense Prediction | Paper Citation Record

Observation 8eb5f3a1-03c5-4fd4-a527-6ae2903425bc · outbound

This paper cites U-net: Convolutional networks for biomedical image segmentation,.

Spatial Lifting for Dense Prediction U-net: Convolutional networks for biomedical image segmentation,

Reference 1

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Observation 95612e38-e35e-4ae8-b779-ef384867f5e9 · outbound

This paper cites Rethinking Atrous Convolution for Semantic Image Segmentation.

Spatial Lifting for Dense Prediction Rethinking Atrous Convolution for Semantic Image Segmentation

Reference 2

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Observation 5aa50f22-4245-4791-9f94-194c6660bad2 · outbound

This paper cites Towards robust monocular depth estimation: Mixing datasets for zero-shot cross- dataset transfer,.

Spatial Lifting for Dense Prediction Towards robust monocular depth estimation: Mixing datasets for zero-shot cross- dataset transfer,

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:45:45.244733Z

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Observation 704836cf-c750-4078-9dcb-3e4e6c9f388f · outbound

This paper cites Adabins: Depth estimation using adaptive bins,.

Spatial Lifting for Dense Prediction Adabins: Depth estimation using adaptive bins,

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:45:45.217038Z

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Observation e15cd16d-14c1-4264-9813-4331b17e50b2 · outbound

This paper cites Raft: Recurrent all-pairs field transforms for optical flow,.

Spatial Lifting for Dense Prediction Raft: Recurrent all-pairs field transforms for optical flow,

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-06T17:45:40.381368Z

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Observation 65653213-32e9-4751-a865-e8eecaa0bc7e · outbound

This paper cites Deep residual learning for image recognition,.

Spatial Lifting for Dense Prediction Deep residual learning for image recognition,

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-06T17:45:40.448860Z

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Observation 1fad1a05-d6cc-4471-9f85-0b8a52354e7a · outbound

This paper cites Fully convolutional networks for semantic segmentation,.

Spatial Lifting for Dense Prediction Fully convolutional networks for semantic segmentation,

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-06T17:45:40.497619Z

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Observation c57a1ef7-57d0-4a70-b2d3-c0dc1e742108 · outbound

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

Spatial Lifting for Dense Prediction An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-06T17:45:40.536624Z

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Observation 124c21a1-689d-49e8-9fe6-dd1eba053cb4 · outbound

This paper cites Segformer: Simple and efficient design for semantic segmentation with transformers,.

Spatial Lifting for Dense Prediction Segformer: Simple and efficient design for semantic segmentation with transformers,

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:45:45.152559Z

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Observation bf0f6f97-34f3-4dc1-a1c2-53c006514a76 · outbound

This paper cites Dropout as a bayesian approximation: Representing model uncertainty in deep learning,.

Spatial Lifting for Dense Prediction Dropout as a bayesian approximation: Representing model uncertainty in deep learning,

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:45:45.122710Z

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Observation 1f6fc1e2-31e5-4d70-b646-d66cb5ef43cc · outbound

This paper cites MobileNets: Efficient Convolutional Neural Networks for Mobile Vision Applications.

Spatial Lifting for Dense Prediction MobileNets: Efficient Convolutional Neural Networks for Mobile Vision Applications

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-06T17:45:40.710792Z

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Observation 56a3e0ea-5e0c-4105-a1ec-afe1afbaa27e · outbound

This paper cites Shufflenet: An extremely efficient convolutional neural network for mobile devices,.

Spatial Lifting for Dense Prediction Shufflenet: An extremely efficient convolutional neural network for mobile devices,

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:45:45.097197Z

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Observation 2cb776fb-bd8a-438c-a700-ca037294e846 · outbound

This paper cites Efficientnet: Rethinking model scaling for convolutional neural networks,.

Spatial Lifting for Dense Prediction Efficientnet: Rethinking model scaling for convolutional neural networks,

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:45:45.072207Z

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Observation 45afff6c-f66b-43b9-8224-d272c9f2eb3a · outbound

This paper cites Learning both weights and connections for efficient neural network,.

Spatial Lifting for Dense Prediction Learning both weights and connections for efficient neural network,

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:45:45.052237Z

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Observation 867227d8-07c6-4eb6-a032-87a961337b4d · outbound

This paper cites Quantizing deep convolutional networks for efficient inference: A whitepaper.

Spatial Lifting for Dense Prediction Quantizing deep convolutional networks for efficient inference: A whitepaper

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-06T17:45:40.956531Z

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Observation f5fbe248-c4bd-4b4f-bf4f-143040b3bbb4 · outbound

This paper cites Training data-efficient image transformers & distillation through attention,.

Spatial Lifting for Dense Prediction Training data-efficient image transformers & distillation through attention,

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:45:45.031496Z

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Observation 92f8215f-9a55-4e67-b703-71d1828f321d · outbound

This paper cites 3d u-net: learning dense volumetric segmentation from sparse annotation,.

Spatial Lifting for Dense Prediction 3d u-net: learning dense volumetric segmentation from sparse annotation,

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:45:45.003667Z

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Observation 7c263d33-8a41-46ad-a4e6-99a135ae1d8a · outbound

This paper cites an unresolved cited work.

Spatial Lifting for Dense Prediction Unresolved cited work

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-06T17:45:40.141495Z

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Observation 3608e417-f1a7-45d1-9d86-15da39662cdb · outbound

This paper cites Pyramid scene parsing network,.

Spatial Lifting for Dense Prediction Pyramid scene parsing network,

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:45:44.985653Z

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Observation 546d8f9a-f85f-4a5d-bf62-fbc4f5135ce3 · outbound

This paper cites Spatial pyramid pooling in deep convolutional networks for visual recognition,.

Spatial Lifting for Dense Prediction Spatial pyramid pooling in deep convolutional networks for visual recognition,

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:45:44.959818Z

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Observation f48ae711-0423-4d11-854d-3cbdb0e326ea · outbound

This paper cites Rethinking semantic segmentation from a sequence-to-sequence perspective with transformers,.

Spatial Lifting for Dense Prediction Rethinking semantic segmentation from a sequence-to-sequence perspective with transformers,

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:45:44.934111Z

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Observation 15caaaeb-dc37-4930-a9a2-c44c88954e6c · outbound

This paper cites The Lottery Ticket Hypothesis: Finding Sparse, Trainable Neural Networks.

Spatial Lifting for Dense Prediction The Lottery Ticket Hypothesis: Finding Sparse, Trainable Neural Networks

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-06T17:45:41.287831Z

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Observation 1cf579c7-82e6-424c-bf2f-3d8e6b889183 · outbound

This paper cites Distilling the Knowledge in a Neural Network.

Spatial Lifting for Dense Prediction Distilling the Knowledge in a Neural Network

Reference 23

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Observation 02c0dd6f-ca8c-460f-ab3e-7974a50b5cb6 · outbound

This paper cites DARTS: Differentiable Architecture Search.

Spatial Lifting for Dense Prediction DARTS: Differentiable Architecture Search

Reference 24

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Observation 57eeed3f-a4bb-4493-94e5-44e36101191c · outbound

This paper cites Mnasnet: Platform-aware neural architecture search for mobile,.

Spatial Lifting for Dense Prediction Mnasnet: Platform-aware neural architecture search for mobile,

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:45:44.909186Z

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Observation 6fbd4024-3cbb-4c7f-bedb-2360be8bf2bd · outbound

This paper cites ProxylessNAS: Direct Neural Architecture Search on Target Task and Hardware.

Spatial Lifting for Dense Prediction ProxylessNAS: Direct Neural Architecture Search on Target Task and Hardware

Reference 26

Resolution: unresolved; no resolver link, observed 2026-08-06T17:45:41.552144Z

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Observation 5d9f7f39-9874-4e4f-a578-87864e37069b · outbound

This paper cites Real-time single image and video super- resolution using an efficient sub-pixel convolutional neural network,.

Spatial Lifting for Dense Prediction Real-time single image and video super- resolution using an efficient sub-pixel convolutional neural network,

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:45:44.883725Z

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Observation a1eaf8df-5ba3-4295-bf5e-313a0c1adb26 · outbound

This paper cites de Berg, Computational geometry: algorithms and applications.

Spatial Lifting for Dense Prediction de Berg, Computational geometry: algorithms and applications

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:45:44.866233Z

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Observation cbd8f366-6312-4cbc-9f51-229e874f9100 · outbound

This paper cites Some Fundamental Aspects about Lipschitz Continuity of Neural Networks.

Spatial Lifting for Dense Prediction Some Fundamental Aspects about Lipschitz Continuity of Neural Networks

Reference 29

Resolution: unresolved; no resolver link, observed 2026-08-06T17:45:41.838809Z

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Observation c355ad97-23f3-4ee9-aee3-d72441654bae · outbound

This paper cites Local rademacher complexities,.

Spatial Lifting for Dense Prediction Local rademacher complexities,

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:45:44.847016Z

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No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 94c5d92b-ae6e-4907-bfdd-fd9dea2bde0f · outbound

This paper cites Pvt v2: Improved baselines with pyramid vision transformer,.

Spatial Lifting for Dense Prediction Pvt v2: Improved baselines with pyramid vision transformer,

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:45:44.827912Z

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Observation bdd1e06f-0836-416b-a34f-6291aa4398b1 · outbound

This paper cites An ensemble classification-based approach applied to retinal blood vessel segmentation,.

Spatial Lifting for Dense Prediction An ensemble classification-based approach applied to retinal blood vessel segmentation,

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:45:44.810785Z

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Observation 72a4afe9-2a35-46d9-99f1-86d15bf7ce40 · outbound

This paper cites Nucleus segmentation across imaging experiments: the 2018 data science bowl,.

Spatial Lifting for Dense Prediction Nucleus segmentation across imaging experiments: the 2018 data science bowl,

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:45:44.784563Z

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Observation 02d419e5-1a56-42f2-a9ea-1d6bac35e65f · outbound

This paper cites Kvasir-seg: A segmented polyp dataset,.

Spatial Lifting for Dense Prediction Kvasir-seg: A segmented polyp dataset,

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:45:44.763994Z

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Observation d26fcca7-83de-4196-a1f2-c04141cae632 · outbound

This paper cites Monusac2020: A multi-organ nuclei segmentation and classification challenge,.

Spatial Lifting for Dense Prediction Monusac2020: A multi-organ nuclei segmentation and classification challenge,

Reference 35

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:45:44.744980Z

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No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation b018e54f-775c-4d25-8141-fc71e059ac18 · outbound

This paper cites an unresolved cited work.

Spatial Lifting for Dense Prediction Unresolved cited work

Reference 36

Resolution: unresolved; raw_fallback, observed 2026-08-06T17:45:44.719688Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 92bb7469-a6f4-4c6c-acc2-76c64a78c04b · outbound

This paper cites The ham10000 dataset, a large collection of multi-source dermatoscopic images of common pigmented skin lesions,.

Spatial Lifting for Dense Prediction The ham10000 dataset, a large collection of multi-source dermatoscopic images of common pigmented skin lesions,

Reference 37

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:45:44.699290Z

Source-reported events for the cited work

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Observation 021cada9-15df-4eac-b21f-c81a15f12254 · outbound

This paper cites A dataset and a technique for generalized nuclear segmentation for computational pathology,.

Spatial Lifting for Dense Prediction A dataset and a technique for generalized nuclear segmentation for computational pathology,

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:45:44.679595Z

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Observation 0c5bef6f-9019-48e9-9caa-a7a02d6de9d8 · outbound

This paper cites Sartorius - cell instance segmentation,.

Spatial Lifting for Dense Prediction Sartorius - cell instance segmentation,

Reference 39

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:45:44.653047Z

Source-reported events for the cited work

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Observation 95165e09-f629-4fda-97a2-a95deac123d5 · outbound

This paper cites Segmentation of nuclei in histopathology images by deep regression of the distance map,.

Spatial Lifting for Dense Prediction Segmentation of nuclei in histopathology images by deep regression of the distance map,

Reference 40

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:45:44.617048Z

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No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 38386222-613b-4909-b6a5-a64c96c6caf1 · outbound

This paper cites Neural control of fasting-induced torpor in mice,.

Spatial Lifting for Dense Prediction Neural control of fasting-induced torpor in mice,

Reference 41

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:45:44.594434Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 3034c849-a775-42dd-902a-68619b397085 · outbound

This paper cites Automating cell counting in fluorescent microscopy through deep learning with c-resunet,.

Spatial Lifting for Dense Prediction Automating cell counting in fluorescent microscopy through deep learning with c-resunet,

Reference 42

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:45:44.574468Z

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Observation 12810336-e20a-4ddb-a42e-08e519fc1746 · outbound

This paper cites Gland segmentation in colon histology images: The glas challenge contest,.

Spatial Lifting for Dense Prediction Gland segmentation in colon histology images: The glas challenge contest,

Reference 43

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:45:44.551610Z

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No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation a34fc21b-b799-473c-bc09-14cb27c248cd · outbound

This paper cites A stochastic polygons model for glandular structures in colon histology images,.

Spatial Lifting for Dense Prediction A stochastic polygons model for glandular structures in colon histology images,

Reference 44

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:45:44.534930Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 63d9a9e4-3d66-4181-a98f-83ae6ba77b26 · outbound

This paper cites Blood cell segmentation dataset,.

Spatial Lifting for Dense Prediction Blood cell segmentation dataset,

Reference 45

Resolution: verified exact; raw_fallback, observed 2026-08-06T17:45:44.096189Z

Source-reported events for the cited work

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Observation 295e1aa0-cf27-42ce-a30f-d68b7be50521 · outbound

This paper cites Fives: A fundus image dataset for artificial intelligence based vessel segmentation,.

Spatial Lifting for Dense Prediction Fives: A fundus image dataset for artificial intelligence based vessel segmentation,

Reference 46

Resolution: unresolved; no resolver link, observed 2026-08-06T17:45:43.540967Z

Source-reported events for the cited work

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Observation 27998cc6-dd7a-4c89-a512-bfd8e3254de7 · outbound

This paper cites Nuinsseg: a fully annotated dataset for nuclei instance segmentation in h&e-stained histological images,.

Spatial Lifting for Dense Prediction Nuinsseg: a fully annotated dataset for nuclei instance segmentation in h&e-stained histological images,

Reference 47

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:45:44.504074Z

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Observation 6fe10078-f66a-4c62-bb28-bcc4393d9a9b · outbound

This paper cites The cityscapes dataset for semantic urban scene understanding,.

Spatial Lifting for Dense Prediction The cityscapes dataset for semantic urban scene understanding,

Reference 48

Resolution: unresolved; no resolver link, observed 2026-08-06T17:45:43.661301Z

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Observation a7d54964-2c12-49b2-b001-f7b10dad2d4b · outbound

This paper cites End-to-end multi-task learning with attention,.

Spatial Lifting for Dense Prediction End-to-end multi-task learning with attention,

Reference 49

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:45:44.470515Z

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No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 5b00cc15-9704-4c1f-9fc9-97c9ba927052 · outbound

This paper cites Learning depth from single monocular images,.

Spatial Lifting for Dense Prediction Learning depth from single monocular images,

Reference 50

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:45:44.452878Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation d6e6a78b-0e14-402d-9bfc-3c30ac01fa2c · outbound

This paper cites Learning 3-d scene structure from a single still image,.

Spatial Lifting for Dense Prediction Learning 3-d scene structure from a single still image,

Reference 51

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:45:44.435769Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 3664ea5c-ab1c-4293-8a06-1de163409da4 · outbound

This paper cites DIODE: A Dense Indoor and Outdoor DEpth Dataset.

Spatial Lifting for Dense Prediction DIODE: A Dense Indoor and Outdoor DEpth Dataset

Reference 52

Resolution: unresolved; no resolver link, observed 2026-08-06T17:45:43.913834Z

Source-reported events for the cited work

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Observation 5307b327-f496-4444-9537-18f71ea2aa4a · outbound

This paper cites Vision meets robotics: The kitti dataset,.

Spatial Lifting for Dense Prediction Vision meets robotics: The kitti dataset,

Reference 53

Resolution: unresolved; no resolver link, observed 2026-08-06T17:45:43.918662Z

Source-reported events for the cited work

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Observation 6ba4c3f1-5b54-4fac-b3b2-e897ee59b624 · outbound

This paper cites Indoor segmentation and support inference from rgbd images,.

Spatial Lifting for Dense Prediction Indoor segmentation and support inference from rgbd images,

Reference 54

Resolution: unresolved; no resolver link, observed 2026-08-06T17:45:43.923048Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 058a5e6c-7822-41d7-8baf-7e12271b75c4 · outbound

This paper cites Modest museum dataset,.

Spatial Lifting for Dense Prediction Modest museum dataset,

Reference 55

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:45:44.392483Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 9e3e24cb-01d9-4bc8-b40e-ec138246202d · outbound

This paper cites Hsnet: A hybrid semantic network for polyp segmentation,.

Spatial Lifting for Dense Prediction Hsnet: A hybrid semantic network for polyp segmentation,

Reference 56

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:45:44.374202Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation c2dd1227-9547-4108-a02d-7a85280e655f · outbound

This paper cites Emcad: Efficient multi- scale convolutional attention decoding for medical image segmentation,.

Spatial Lifting for Dense Prediction Emcad: Efficient multi- scale convolutional attention decoding for medical image segmentation,

Reference 57

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This paper cites Medical image segmentation via cascaded attention decoding,.

Spatial Lifting for Dense Prediction Medical image segmentation via cascaded attention decoding,

Reference 58

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:45:44.333563Z

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This paper cites Mobilenetv2: Inverted residuals and linear bottlenecks,.

Spatial Lifting for Dense Prediction Mobilenetv2: Inverted residuals and linear bottlenecks,

Reference 59

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This paper cites Aggregated residual transformations for deep neural networks,.

Spatial Lifting for Dense Prediction Aggregated residual transformations for deep neural networks,

Reference 60

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:45:44.304071Z

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This paper cites Fastdepth: Fast monocular depth estimation on embedded systems,.

Spatial Lifting for Dense Prediction Fastdepth: Fast monocular depth estimation on embedded systems,

Reference 61

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:45:44.284787Z

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