Leveraging Sparse LiDAR for RAFT-Stereo: A Depth Pre-Fill Perspective | Paper Citation Record

Observation eedb7a0c-5c0c-4737-8c96-734f411252ca · outbound

This paper cites Raft-stereo: Multilevel recurrent field transforms for stereo matching.

Leveraging Sparse LiDAR for RAFT-Stereo: A Depth Pre-Fill Perspective Raft-stereo: Multilevel recurrent field transforms for stereo matching

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T14:09:12.070695Z

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Observation ab17bd5d-1e91-4044-ac48-123533526d37 · outbound

This paper cites Iterative geometry encoding volume for stereo matching.

Leveraging Sparse LiDAR for RAFT-Stereo: A Depth Pre-Fill Perspective Iterative geometry encoding volume for stereo matching

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T14:09:12.057732Z

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Observation bf4e031c-2a5e-4955-a055-dfc89d1ffb9c · outbound

This paper cites Selective-stereo: Adaptive frequency information selection for stereo matching.

Leveraging Sparse LiDAR for RAFT-Stereo: A Depth Pre-Fill Perspective Selective-stereo: Adaptive frequency information selection for stereo matching

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T14:09:12.043314Z

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Observation 54b3ad6d-e2d1-47e5-850c-e7fa026c49ab · outbound

This paper cites Practical stereo matching via cascaded recurrent network with adaptive correlation.

Leveraging Sparse LiDAR for RAFT-Stereo: A Depth Pre-Fill Perspective Practical stereo matching via cascaded recurrent network with adaptive correlation

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T14:09:12.027125Z

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Observation f47be03f-eff0-4c34-b195-58a6f1635b52 · outbound

This paper cites Pyramid stereo matching network.

Leveraging Sparse LiDAR for RAFT-Stereo: A Depth Pre-Fill Perspective Pyramid stereo matching network

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T14:09:12.012001Z

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Observation 3dc30664-3c81-44cd-9e72-749c54fa4af5 · outbound

This paper cites End-to-end learning of geometry and context for deep stereo regression.

Leveraging Sparse LiDAR for RAFT-Stereo: A Depth Pre-Fill Perspective End-to-end learning of geometry and context for deep stereo regression

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T14:09:11.997963Z

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Observation 69c81824-7a2f-4609-90e5-bac1e8fbfb7e · outbound

This paper cites Hierarchical deep stereo matching on high-resolution images.

Leveraging Sparse LiDAR for RAFT-Stereo: A Depth Pre-Fill Perspective Hierarchical deep stereo matching on high-resolution images

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T14:09:11.984310Z

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Observation a75cc4cb-edad-438f-9036-33acb1710112 · outbound

This paper cites Revisiting stereo depth estimation from a sequence-to-sequence perspective with transformers.

Leveraging Sparse LiDAR for RAFT-Stereo: A Depth Pre-Fill Perspective Revisiting stereo depth estimation from a sequence-to-sequence perspective with transformers

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T14:09:11.970475Z

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Observation 5eeb1847-9443-4b2a-9d41-ba442a204ca0 · outbound

This paper cites Context-enhanced stereo transformer.

Leveraging Sparse LiDAR for RAFT-Stereo: A Depth Pre-Fill Perspective Context-enhanced stereo transformer

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T14:09:11.957062Z

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Observation 4ae9ba4a-8200-493d-bddc-c192b658d25d · outbound

This paper cites V olumetric propagation network: Stereo-lidar fusion for long-range depth estimation.

Leveraging Sparse LiDAR for RAFT-Stereo: A Depth Pre-Fill Perspective V olumetric propagation network: Stereo-lidar fusion for long-range depth estimation

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T14:09:11.943490Z

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Observation 444bfacf-3943-46c9-90ea-0c2ce5dc0a32 · outbound

This paper cites Expanding sparse lidar depth and guiding stereo matching for robust dense depth estimation.

Leveraging Sparse LiDAR for RAFT-Stereo: A Depth Pre-Fill Perspective Expanding sparse lidar depth and guiding stereo matching for robust dense depth estimation

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T14:09:11.929440Z

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Observation d7f561fe-57f5-4e7b-ade5-26ec47155119 · outbound

This paper cites Stereo-lidar depth estimation with deformable propagation and learned disparity-depth conversion.

Leveraging Sparse LiDAR for RAFT-Stereo: A Depth Pre-Fill Perspective Stereo-lidar depth estimation with deformable propagation and learned disparity-depth conversion

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T14:09:11.915721Z

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Observation 2f1b3adb-76aa-486f-9c90-284604ffb3e9 · outbound

This paper cites Sparse lidar assisted self-supervised stereo disparity estimation.

Leveraging Sparse LiDAR for RAFT-Stereo: A Depth Pre-Fill Perspective Sparse lidar assisted self-supervised stereo disparity estimation

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T14:09:11.902108Z

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Observation ed7184d3-36d7-43e2-bcc3-6c57029a182f · outbound

This paper cites Sparsity invariant cnns.

Leveraging Sparse LiDAR for RAFT-Stereo: A Depth Pre-Fill Perspective Sparsity invariant cnns

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T14:09:11.887776Z

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Observation e728cec1-0ea6-4ac4-b817-703235d3eb4c · outbound

This paper cites Are we ready for autonomous driving? the kitti vision benchmark suite.

Leveraging Sparse LiDAR for RAFT-Stereo: A Depth Pre-Fill Perspective Are we ready for autonomous driving? the kitti vision benchmark suite

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T14:09:11.873645Z

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Observation 9af90f94-8e21-4dcd-ac5d-200e5681160c · outbound

This paper cites In defense of classical image processing: Fast depth completion on the cpu.

Leveraging Sparse LiDAR for RAFT-Stereo: A Depth Pre-Fill Perspective In defense of classical image processing: Fast depth completion on the cpu

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T14:09:11.859276Z

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Observation 2fd6d83c-c0e5-4fea-ba72-8e077f908dec · outbound

This paper cites Virtual KITTI 2.

Leveraging Sparse LiDAR for RAFT-Stereo: A Depth Pre-Fill Perspective Virtual KITTI 2

Reference 17

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Observation e6170da3-e71a-49a7-ae48-8eb6c7afb925 · outbound

This paper cites Deep depth estimation from thermal image.

Leveraging Sparse LiDAR for RAFT-Stereo: A Depth Pre-Fill Perspective Deep depth estimation from thermal image

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T14:09:11.845992Z

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Observation 8cdde0ad-efb8-4336-94a8-3acfa38c7c78 · outbound

This paper cites Non-parametric local transforms for computing visual corre- spondence.

Leveraging Sparse LiDAR for RAFT-Stereo: A Depth Pre-Fill Perspective Non-parametric local transforms for computing visual corre- spondence

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T14:09:11.831585Z

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Observation ab14bbce-0537-4a36-97d7-7c7f8a108716 · outbound

This paper cites A constant-space belief propagation algorithm for stereo matching.

Leveraging Sparse LiDAR for RAFT-Stereo: A Depth Pre-Fill Perspective A constant-space belief propagation algorithm for stereo matching

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T14:09:11.818242Z

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Observation 321ce29c-3f3a-4e25-94f8-71bbd431232b · outbound

This paper cites Stereo correspondence by dynamic programming on a tree.

Leveraging Sparse LiDAR for RAFT-Stereo: A Depth Pre-Fill Perspective Stereo correspondence by dynamic programming on a tree

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T14:09:11.805045Z

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Observation 08d18773-a336-4650-991d-f4f3afd0decc · outbound

This paper cites Stereo matching with color-weighted correlation, hierarchical belief propagation, and occlusion han- dling.

Leveraging Sparse LiDAR for RAFT-Stereo: A Depth Pre-Fill Perspective Stereo matching with color-weighted correlation, hierarchical belief propagation, and occlusion han- dling

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T14:09:11.791366Z

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Observation bc5d2484-2f3b-4350-987d-c7faca390bea · outbound

This paper cites Stereo processing by semiglobal matching and mutual information.TPAMI, 2007.

Leveraging Sparse LiDAR for RAFT-Stereo: A Depth Pre-Fill Perspective Stereo processing by semiglobal matching and mutual information.TPAMI, 2007

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T14:09:11.776850Z

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Observation b1efbb14-ca9c-4a07-a22d-22a9734fc1af · outbound

This paper cites Nerf-supervised deep stereo.

Leveraging Sparse LiDAR for RAFT-Stereo: A Depth Pre-Fill Perspective Nerf-supervised deep stereo

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T14:09:11.763464Z

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Observation f6dfee1f-7e00-4c35-a3d3-ef72e0cf9db5 · outbound

This paper cites Domain generalized stereo matching via hierarchical visual transformation.

Leveraging Sparse LiDAR for RAFT-Stereo: A Depth Pre-Fill Perspective Domain generalized stereo matching via hierarchical visual transformation

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T14:09:11.750128Z

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Observation c213c267-945d-4b1e-bc57-db6c72428f83 · outbound

This paper cites Croco v2: Improved cross-view completion pre-training for stereo matching and optical flow.

Leveraging Sparse LiDAR for RAFT-Stereo: A Depth Pre-Fill Perspective Croco v2: Improved cross-view completion pre-training for stereo matching and optical flow

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T14:09:11.736159Z

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Observation 10a91afb-d89b-4f27-ba5a-6ff7ce5ea3a5 · outbound

This paper cites Graftnet: Towards domain generalized stereo matching with a broad-spectrum and task-oriented feature.

Leveraging Sparse LiDAR for RAFT-Stereo: A Depth Pre-Fill Perspective Graftnet: Towards domain generalized stereo matching with a broad-spectrum and task-oriented feature

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T14:09:11.722285Z

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Observation 25c42e6a-37e1-49fc-b38e-790f78469271 · outbound

This paper cites Uncertainty guided adaptive warping for robust and efficient stereo matching.

Leveraging Sparse LiDAR for RAFT-Stereo: A Depth Pre-Fill Perspective Uncertainty guided adaptive warping for robust and efficient stereo matching

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T14:09:11.707918Z

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Observation 0e1f43d7-c204-42f5-b180-1a5491880b19 · outbound

This paper cites Dps-net: Deep polarimetric stereo depth estimation.

Leveraging Sparse LiDAR for RAFT-Stereo: A Depth Pre-Fill Perspective Dps-net: Deep polarimetric stereo depth estimation

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T14:09:11.595860Z

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Observation 46e41f91-9719-4d90-ba13-5f771519e3f1 · outbound

This paper cites Federated online adaptation for deep stereo.

Leveraging Sparse LiDAR for RAFT-Stereo: A Depth Pre-Fill Perspective Federated online adaptation for deep stereo

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T14:09:11.252788Z

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Observation d33c7a81-699e-4df4-829d-8812271f4e32 · outbound

This paper cites Accurate and efficient stereo matching via attention concatenation volume.

Leveraging Sparse LiDAR for RAFT-Stereo: A Depth Pre-Fill Perspective Accurate and efficient stereo matching via attention concatenation volume

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T14:09:11.042042Z

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Observation a2ed7afd-a7ae-4daf-babb-b5c392fd0ba7 · outbound

This paper cites Active stereo without pattern projector.

Leveraging Sparse LiDAR for RAFT-Stereo: A Depth Pre-Fill Perspective Active stereo without pattern projector

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T14:09:10.815080Z

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Observation 974da2e6-5bbd-4193-9eeb-d1be073aee39 · outbound

This paper cites Neural markov random field for stereo matching.

Leveraging Sparse LiDAR for RAFT-Stereo: A Depth Pre-Fill Perspective Neural markov random field for stereo matching

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T14:09:10.556122Z

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Observation d720fbfe-5403-4781-b7eb-d2b45395cb84 · outbound

This paper cites OpenStereo: A Comprehensive Benchmark for Stereo Matching and Strong Baseline.

Leveraging Sparse LiDAR for RAFT-Stereo: A Depth Pre-Fill Perspective OpenStereo: A Comprehensive Benchmark for Stereo Matching and Strong Baseline

Reference 34

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Observation 33b2cd91-dc50-4d94-ab42-344ec6c00453 · outbound

This paper cites Segstereo: Exploiting semantic information for disparity estimation.

Leveraging Sparse LiDAR for RAFT-Stereo: A Depth Pre-Fill Perspective Segstereo: Exploiting semantic information for disparity estimation

Reference 35

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T14:09:10.367163Z

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Observation 5747e4cb-dff8-411d-8444-dfc73ffff714 · outbound

This paper cites An image is worth 16x16 words: Transformers for image recognition at scale.

Leveraging Sparse LiDAR for RAFT-Stereo: A Depth Pre-Fill Perspective An image is worth 16x16 words: Transformers for image recognition at scale

Reference 36

Resolution: unresolved; no resolver link, observed 2026-08-06T14:09:03.855630Z

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Observation a83b0c42-ea4c-452a-8da4-551056076649 · outbound

This paper cites High-frequency stereo matching network.

Leveraging Sparse LiDAR for RAFT-Stereo: A Depth Pre-Fill Perspective High-frequency stereo matching network

Reference 37

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T14:09:10.207233Z

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Observation 4f47571e-366b-4540-84bb-47f74998a7df · outbound

This paper cites Eai-stereo: Error aware iterative network for stereo matching.

Leveraging Sparse LiDAR for RAFT-Stereo: A Depth Pre-Fill Perspective Eai-stereo: Error aware iterative network for stereo matching

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T14:09:10.027503Z

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Observation 096b2990-35ba-4cc2-859d-dacb5e89abb9 · outbound

This paper cites Parameterized cost volume for stereo matching.

Leveraging Sparse LiDAR for RAFT-Stereo: A Depth Pre-Fill Perspective Parameterized cost volume for stereo matching

Reference 39

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T14:09:09.824671Z

Source-reported events for the cited work

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Observation 474a5764-774f-4f8c-a56b-7340830829d3 · outbound

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

Leveraging Sparse LiDAR for RAFT-Stereo: A Depth Pre-Fill Perspective Raft: Recurrent all-pairs field transforms for optical flow

Reference 40

Resolution: unresolved; no resolver link, observed 2026-08-06T14:09:04.145855Z

Source-reported events for the cited work

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Observation b43093ab-174d-4b84-b3f1-57be32d44a46 · outbound

This paper cites Noise-aware unsupervised deep lidar-stereo fusion.

Leveraging Sparse LiDAR for RAFT-Stereo: A Depth Pre-Fill Perspective Noise-aware unsupervised deep lidar-stereo fusion

Reference 41

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T14:09:09.630815Z

Source-reported events for the cited work

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Observation 3aa3e6df-a4bb-40a1-ac04-b130dd63878c · outbound

This paper cites Sparse lidar and stereo fusion (sls-fusion) for depth estimation and 3d object detection.

Leveraging Sparse LiDAR for RAFT-Stereo: A Depth Pre-Fill Perspective Sparse lidar and stereo fusion (sls-fusion) for depth estimation and 3d object detection

Reference 42

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T14:09:09.452109Z

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Observation e7c2e330-1455-417c-947b-abc64b193d46 · outbound

This paper cites 3d lidar and stereo fusion using stereo matching network with conditional cost volume normalization.

Leveraging Sparse LiDAR for RAFT-Stereo: A Depth Pre-Fill Perspective 3d lidar and stereo fusion using stereo matching network with conditional cost volume normalization

Reference 43

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T14:09:09.262802Z

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

Observation 7ec346ca-46d0-4ab9-8518-193a1c391420 · outbound

This paper cites Slfnet: A stereo and lidar fusion network for depth completion.

Leveraging Sparse LiDAR for RAFT-Stereo: A Depth Pre-Fill Perspective Slfnet: A stereo and lidar fusion network for depth completion

Reference 44

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T14:09:09.100587Z

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 7412f90a-36f8-471e-9c47-dcf3adb22917 · outbound

This paper cites Expansion of visual hints for improved generalization in stereo matching.

Leveraging Sparse LiDAR for RAFT-Stereo: A Depth Pre-Fill Perspective Expansion of visual hints for improved generalization in stereo matching

Reference 45

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T14:09:08.915167Z

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 bf16d228-7fe6-42e3-aed9-316fc38da9c9 · outbound

This paper cites Guided stereo matching.

Leveraging Sparse LiDAR for RAFT-Stereo: A Depth Pre-Fill Perspective Guided stereo matching

Reference 46

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T14:09:08.776786Z

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 66c72b51-d282-4079-a65a-55b25dae757d · outbound

This paper cites S3: Learnable sparse signal superdensity for guided depth estimation.

Leveraging Sparse LiDAR for RAFT-Stereo: A Depth Pre-Fill Perspective S3: Learnable sparse signal superdensity for guided depth estimation

Reference 47

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T14:09:08.626045Z

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 954dca2b-828e-44eb-8273-7b9b41b76c40 · outbound

This paper cites High-precision depth estimation with the 3d lidar and stereo fusion.

Leveraging Sparse LiDAR for RAFT-Stereo: A Depth Pre-Fill Perspective High-precision depth estimation with the 3d lidar and stereo fusion

Reference 48

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T14:09:08.465262Z

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 b55e1700-be96-48fd-aa48-aa754820aaa1 · outbound

This paper cites Listereo: Generate dense depth maps from lidar and stereo imagery.

Leveraging Sparse LiDAR for RAFT-Stereo: A Depth Pre-Fill Perspective Listereo: Generate dense depth maps from lidar and stereo imagery

Reference 49

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T14:09:08.309000Z

Source-reported events for the cited work

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Observation 08cc41b4-475f-4a17-9780-614fd6aca674 · outbound

This paper cites Dfusenet: Deep fusion of rgb and sparse depth information for image guided dense depth completion.

Leveraging Sparse LiDAR for RAFT-Stereo: A Depth Pre-Fill Perspective Dfusenet: Deep fusion of rgb and sparse depth information for image guided dense depth completion

Reference 50

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T14:09:08.147250Z

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 3aec04e8-bd5f-40e4-89b7-3c2d5f69cbf9 · outbound

This paper cites Deeplidar: Deep surface normal guided depth prediction for outdoor scene from sparse lidar data and single color image.

Leveraging Sparse LiDAR for RAFT-Stereo: A Depth Pre-Fill Perspective Deeplidar: Deep surface normal guided depth prediction for outdoor scene from sparse lidar data and single color image

Reference 51

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T14:09:08.009942Z

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 74145847-0e77-42bd-8f11-c849ac93b733 · outbound

This paper cites Penet: Towards precise and efficient image guided depth completion.

Leveraging Sparse LiDAR for RAFT-Stereo: A Depth Pre-Fill Perspective Penet: Towards precise and efficient image guided depth completion

Reference 52

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T14:09:07.851081Z

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 ff337232-b607-4217-bba2-d4e03a55eb69 · outbound

This paper cites Learning guided convolutional network for depth completion.

Leveraging Sparse LiDAR for RAFT-Stereo: A Depth Pre-Fill Perspective Learning guided convolutional network for depth completion

Reference 53

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T14:09:07.688458Z

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 1f36e94b-65bf-4c69-b4ed-1000e4a1b3c6 · outbound

This paper cites Mff-net: Towards efficient monocular depth completion with multi-modal feature fusion.

Leveraging Sparse LiDAR for RAFT-Stereo: A Depth Pre-Fill Perspective Mff-net: Towards efficient monocular depth completion with multi-modal feature fusion

Reference 54

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T14:09:07.537372Z

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 9e14f238-d0e5-4cfe-afa9-375c737a2f65 · outbound

This paper cites Non-local spatial propagation network for depth completion.

Leveraging Sparse LiDAR for RAFT-Stereo: A Depth Pre-Fill Perspective Non-local spatial propagation network for depth completion

Reference 55

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T14:09:07.407880Z

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 05afeb41-0425-4bd9-9b3d-f26f29056de9 · outbound

This paper cites Learning affinity via spatial propagation networks.

Leveraging Sparse LiDAR for RAFT-Stereo: A Depth Pre-Fill Perspective Learning affinity via spatial propagation networks

Reference 56

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T14:09:07.230973Z

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 4d3113b9-103b-4b33-90bd-91b0847fa8e0 · outbound

This paper cites Depth estimation via affinity learned with convolutional spatial propagation network.

Leveraging Sparse LiDAR for RAFT-Stereo: A Depth Pre-Fill Perspective Depth estimation via affinity learned with convolutional spatial propagation network

Reference 57

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T14:09:07.120601Z

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 80eaa1b7-6291-48bf-a01c-51a3fb07d302 · outbound

This paper cites Lrru: Long-short range recurrent updating networks for depth completion.

Leveraging Sparse LiDAR for RAFT-Stereo: A Depth Pre-Fill Perspective Lrru: Long-short range recurrent updating networks for depth completion

Reference 58

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T14:09:06.960552Z

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 67bde3f4-b853-49da-b1c7-1888213ad8ce · outbound

This paper cites Fcfr-net: Feature fusion based coarse-to-fine residual learning for depth completion.

Leveraging Sparse LiDAR for RAFT-Stereo: A Depth Pre-Fill Perspective Fcfr-net: Feature fusion based coarse-to-fine residual learning for depth completion

Reference 59

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T14:09:06.831378Z

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 947521bd-01c3-4740-8adb-e27ef2c06b82 · outbound

This paper cites Deep residual learning for image recognition.

Leveraging Sparse LiDAR for RAFT-Stereo: A Depth Pre-Fill Perspective Deep residual learning for image recognition

Reference 60

Resolution: unresolved; no resolver link, observed 2026-08-06T14:09:05.590730Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 828fbdf0-2e51-435a-adf7-c4ac071039d6 · outbound

This paper cites Pseudo-lidar++: Accurate depth for 3d object detection in autonomous driving.

Leveraging Sparse LiDAR for RAFT-Stereo: A Depth Pre-Fill Perspective Pseudo-lidar++: Accurate depth for 3d object detection in autonomous driving

Reference 61

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T14:09:06.684397Z

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 73bd20ce-4ea3-42bf-a1fc-1c2589f89ef3 · outbound

This paper cites Sea-raft: Simple, efficient, accurate raft for optical flow.

Leveraging Sparse LiDAR for RAFT-Stereo: A Depth Pre-Fill Perspective Sea-raft: Simple, efficient, accurate raft for optical flow

Reference 62

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T14:09:06.543828Z

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 3dc20902-fbd3-4012-bf50-265125d60069 · outbound

This paper cites A surface geometry model for lidar depth completion.

Leveraging Sparse LiDAR for RAFT-Stereo: A Depth Pre-Fill Perspective A surface geometry model for lidar depth completion

Reference 63

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T14:09:06.389762Z

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 5cef189b-d54f-493a-948a-7660e4c7d403 · outbound

This paper cites Fpga accelerated real-time recurrent all-pairs field transforms for optical flow.

Leveraging Sparse LiDAR for RAFT-Stereo: A Depth Pre-Fill Perspective Fpga accelerated real-time recurrent all-pairs field transforms for optical flow

Reference 64

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T14:09:06.240155Z

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 52bae811-4ec3-415c-8672-0c4ed0e04c23 · outbound

This paper cites Scene01.

Leveraging Sparse LiDAR for RAFT-Stereo: A Depth Pre-Fill Perspective Scene01

Reference 65

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T14:09:06.084531Z

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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Outbound references

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