Dense-depth map guided deep Lidar-Visual Odometry with Sparse Point Clouds and Images | Paper Citation Record

Observation 7f80d67f-40ea-4081-b86a-fea014065f13 · outbound

This paper cites Lio-sam: Tightly-coupled lidar inertial odometry via smoothing and mapping,.

Dense-depth map guided deep Lidar-Visual Odometry with Sparse Point Clouds and Images Lio-sam: Tightly-coupled lidar inertial odometry via smoothing and mapping,

Reference 1

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This paper cites Visual-lidar odometry and mapping: Low-drift, robust, and fast,.

Dense-depth map guided deep Lidar-Visual Odometry with Sparse Point Clouds and Images Visual-lidar odometry and mapping: Low-drift, robust, and fast,

Reference 2

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This paper cites Self-supervised visual- lidar odometry with flip consistency,.

Dense-depth map guided deep Lidar-Visual Odometry with Sparse Point Clouds and Images Self-supervised visual- lidar odometry with flip consistency,

Reference 3

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This paper cites Cnn-slam: Real-time dense monocular slam with learned depth prediction,.

Dense-depth map guided deep Lidar-Visual Odometry with Sparse Point Clouds and Images Cnn-slam: Real-time dense monocular slam with learned depth prediction,

Reference 4

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This paper cites Pwc-net: Cnns for optical flow using pyramid, warping, and cost volume,.

Dense-depth map guided deep Lidar-Visual Odometry with Sparse Point Clouds and Images Pwc-net: Cnns for optical flow using pyramid, warping, and cost volume,

Reference 5

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Observation 98ad9503-d6e0-4c45-941b-9599550a2557 · outbound

This paper cites Lidar odometry and mapping based on semantic information for outdoor environment,.

Dense-depth map guided deep Lidar-Visual Odometry with Sparse Point Clouds and Images Lidar odometry and mapping based on semantic information for outdoor environment,

Reference 6

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This paper cites Loam: Lidar odometry and mapping in real- time.

Dense-depth map guided deep Lidar-Visual Odometry with Sparse Point Clouds and Images Loam: Lidar odometry and mapping in real- time

Reference 7

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This paper cites Lego-loam: Lightweight and ground-optimized lidar odometry and mapping on variable terrain,.

Dense-depth map guided deep Lidar-Visual Odometry with Sparse Point Clouds and Images Lego-loam: Lightweight and ground-optimized lidar odometry and mapping on variable terrain,

Reference 8

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Observation c6e51ffd-4080-4ae7-a9f2-9531df435948 · outbound

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

Dense-depth map guided deep Lidar-Visual Odometry with Sparse Point Clouds and Images Vision meets robotics: The kitti dataset,

Reference 9

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Observation 51e3ae7c-017a-498d-8741-351f2a9cf0ee · outbound

This paper cites Depth completion from sparse lidar data with depth-normal constraints,.

Dense-depth map guided deep Lidar-Visual Odometry with Sparse Point Clouds and Images Depth completion from sparse lidar data with depth-normal constraints,

Reference 10

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This paper cites Attention is all you need,.

Dense-depth map guided deep Lidar-Visual Odometry with Sparse Point Clouds and Images Attention is all you need,

Reference 11

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

Dense-depth map guided deep Lidar-Visual Odometry with Sparse Point Clouds and Images Are we ready for autonomous driving? the kitti vision benchmark suite,

Reference 12

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This paper cites Orb-slam: a versatile and accurate monocular slam system,.

Dense-depth map guided deep Lidar-Visual Odometry with Sparse Point Clouds and Images Orb-slam: a versatile and accurate monocular slam system,

Reference 13

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This paper cites Orb-slam2: An open-source slam system for monocular, stereo, and rgb-d cameras,.

Dense-depth map guided deep Lidar-Visual Odometry with Sparse Point Clouds and Images Orb-slam2: An open-source slam system for monocular, stereo, and rgb-d cameras,

Reference 14

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Observation 4f5e4043-9286-4cb6-95a2-d478f255f7e4 · outbound

This paper cites Direct sparse odometry,.

Dense-depth map guided deep Lidar-Visual Odometry with Sparse Point Clouds and Images Direct sparse odometry,

Reference 15

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This paper cites Dtam: Dense tracking and mapping in real-time,.

Dense-depth map guided deep Lidar-Visual Odometry with Sparse Point Clouds and Images Dtam: Dense tracking and mapping in real-time,

Reference 16

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Observation c2dc0b9e-bc6f-42e8-aa5b-96aa051fe6f4 · outbound

This paper cites Lsd-slam: Large-scale direct monocular slam,.

Dense-depth map guided deep Lidar-Visual Odometry with Sparse Point Clouds and Images Lsd-slam: Large-scale direct monocular slam,

Reference 17

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Observation c11a6f8d-58d9-4406-b6e4-3d04b51bddd8 · outbound

This paper cites Deepvo: Towards end-to- end visual odometry with deep recurrent convolutional neural networks,.

Dense-depth map guided deep Lidar-Visual Odometry with Sparse Point Clouds and Images Deepvo: Towards end-to- end visual odometry with deep recurrent convolutional neural networks,

Reference 18

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Observation c3902ca7-4235-40df-ba29-81360f7f27b9 · outbound

This paper cites DF-VO: What Should Be Learnt for Visual Odometry?.

Dense-depth map guided deep Lidar-Visual Odometry with Sparse Point Clouds and Images DF-VO: What Should Be Learnt for Visual Odometry?

Reference 19

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

Dense-depth map guided deep Lidar-Visual Odometry with Sparse Point Clouds and Images Raft: Recurrent all-pairs field transforms for op- tical flow,

Reference 20

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Observation 65dad3a1-5f76-4510-9f36-ae56accf8d63 · outbound

This paper cites Unsupervised learning of monocular depth estimation and visual odom- etry with deep feature reconstruction,.

Dense-depth map guided deep Lidar-Visual Odometry with Sparse Point Clouds and Images Unsupervised learning of monocular depth estimation and visual odom- etry with deep feature reconstruction,

Reference 21

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This paper cites D3vo: Deep depth, deep pose and deep uncertainty for monocular visual odometry,.

Dense-depth map guided deep Lidar-Visual Odometry with Sparse Point Clouds and Images D3vo: Deep depth, deep pose and deep uncertainty for monocular visual odometry,

Reference 22

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This paper cites Method for registration of 3-d shapes,.

Dense-depth map guided deep Lidar-Visual Odometry with Sparse Point Clouds and Images Method for registration of 3-d shapes,

Reference 23

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Observation 97d49b7c-5941-467a-8176-d57c443bbf55 · outbound

This paper cites Tightly coupled 3d lidar inertial odometry and mapping,.

Dense-depth map guided deep Lidar-Visual Odometry with Sparse Point Clouds and Images Tightly coupled 3d lidar inertial odometry and mapping,

Reference 24

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Observation aeb5c84c-f293-4799-8067-135693592c75 · outbound

This paper cites Lo- net: Deep real-time lidar odometry,.

Dense-depth map guided deep Lidar-Visual Odometry with Sparse Point Clouds and Images Lo- net: Deep real-time lidar odometry,

Reference 25

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Observation 7d3f05f7-3b66-4458-a0c3-be45a8173256 · outbound

This paper cites DeepLO: Geometry-Aware Deep LiDAR Odometry.

Dense-depth map guided deep Lidar-Visual Odometry with Sparse Point Clouds and Images DeepLO: Geometry-Aware Deep LiDAR Odometry

Reference 26

Resolution: verified exact; local_arxiv, observed 2026-08-06T15:35:19.103120Z

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This paper cites Pwclo-net: Deep lidar odometry in 3d point clouds using hierarchical embedding mask optimization,.

Dense-depth map guided deep Lidar-Visual Odometry with Sparse Point Clouds and Images Pwclo-net: Deep lidar odometry in 3d point clouds using hierarchical embedding mask optimization,

Reference 27

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This paper cites Lodonet: A deep neural network with 2d keypoint matching for 3d lidar odometry estimation,.

Dense-depth map guided deep Lidar-Visual Odometry with Sparse Point Clouds and Images Lodonet: A deep neural network with 2d keypoint matching for 3d lidar odometry estimation,

Reference 28

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Observation 95ddcd3e-d110-4e0d-a1ce-47c53c3255ae · outbound

This paper cites Illumination invariant imaging: Applications in robust vision-based localisation, mapping and classification for autonomous vehicles,.

Dense-depth map guided deep Lidar-Visual Odometry with Sparse Point Clouds and Images Illumination invariant imaging: Applications in robust vision-based localisation, mapping and classification for autonomous vehicles,

Reference 29

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Observation 70da1640-23f5-4c9d-b083-cc4bfddf0695 · outbound

This paper cites Dvlo: Deep visual-lidar odometry with local-to-global feature fusion and bi- directional structure alignment,.

Dense-depth map guided deep Lidar-Visual Odometry with Sparse Point Clouds and Images Dvlo: Deep visual-lidar odometry with local-to-global feature fusion and bi- directional structure alignment,

Reference 30

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This paper cites Visual-lidar slam based on unsu- pervised multi-channel deep neural networks,.

Dense-depth map guided deep Lidar-Visual Odometry with Sparse Point Clouds and Images Visual-lidar slam based on unsu- pervised multi-channel deep neural networks,

Reference 31

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

Dense-depth map guided deep Lidar-Visual Odometry with Sparse Point Clouds and Images Penet: Towards precise and efficient image guided depth completion,

Reference 32

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Observation c9239060-1458-432f-9f67-ed248afd8e07 · outbound

This paper cites Squeeze-and-excitation networks,.

Dense-depth map guided deep Lidar-Visual Odometry with Sparse Point Clouds and Images Squeeze-and-excitation networks,

Reference 33

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This paper cites Cbam: Convolutional block attention module,.

Dense-depth map guided deep Lidar-Visual Odometry with Sparse Point Clouds and Images Cbam: Convolutional block attention module,

Reference 34

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This paper cites Liteflownet: A lightweight convo- lutional neural network for optical flow estimation,.

Dense-depth map guided deep Lidar-Visual Odometry with Sparse Point Clouds and Images Liteflownet: A lightweight convo- lutional neural network for optical flow estimation,

Reference 35

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Observation 9792c978-bfc7-4f18-8381-b42cefa50e0c · outbound

This paper cites Maskflownet: Asymmetric feature matching with learnable occlusion mask,.

Dense-depth map guided deep Lidar-Visual Odometry with Sparse Point Clouds and Images Maskflownet: Asymmetric feature matching with learnable occlusion mask,

Reference 36

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:35:19.229132Z

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Observation 46ab984e-98ab-425e-91e2-9f24a0a09fac · outbound

This paper cites Just go with the flow: Self-supervised scene flow estimation,.

Dense-depth map guided deep Lidar-Visual Odometry with Sparse Point Clouds and Images Just go with the flow: Self-supervised scene flow estimation,

Reference 37

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This paper cites Rethinking optical flow from geometric matching consistent perspective,.

Dense-depth map guided deep Lidar-Visual Odometry with Sparse Point Clouds and Images Rethinking optical flow from geometric matching consistent perspective,

Reference 38

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Observation 6f56942c-0c0a-4e96-b358-e03935ef8b71 · outbound

This paper cites Depth- aware video frame interpolation,.

Dense-depth map guided deep Lidar-Visual Odometry with Sparse Point Clouds and Images Depth- aware video frame interpolation,

Reference 39

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Observation e6a88bb9-8196-4e0c-a089-5d1b19c80860 · outbound

This paper cites Unsupervised learning of depth and ego-motion from video,.

Dense-depth map guided deep Lidar-Visual Odometry with Sparse Point Clouds and Images Unsupervised learning of depth and ego-motion from video,

Reference 40

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:35:19.201302Z

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Observation a4736c0e-09d2-4024-a2cf-991bfe8f84a2 · outbound

This paper cites Generalizing to the open world: Deep visual odometry with online adaptation,.

Dense-depth map guided deep Lidar-Visual Odometry with Sparse Point Clouds and Images Generalizing to the open world: Deep visual odometry with online adaptation,

Reference 41

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Observation bc921045-f3ce-4ee5-8cfd-e5fb1e535cf1 · outbound

This paper cites H-vlo: hybrid lidar-camera fusion for self-supervised odometry,.

Dense-depth map guided deep Lidar-Visual Odometry with Sparse Point Clouds and Images H-vlo: hybrid lidar-camera fusion for self-supervised odometry,

Reference 42

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Observation 3edab751-962a-4018-976e-6cac49115902 · outbound

This paper cites Dvl-slam: Sparse depth enhanced direct visual-lidar slam,.

Dense-depth map guided deep Lidar-Visual Odometry with Sparse Point Clouds and Images Dvl-slam: Sparse depth enhanced direct visual-lidar slam,

Reference 43

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:35:19.177219Z

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Observation 0efeaedd-b9a6-41f0-a1b9-97fe8e966a0a · outbound

This paper cites Lidar- monocular visual odometry using point and line features,.

Dense-depth map guided deep Lidar-Visual Odometry with Sparse Point Clouds and Images Lidar- monocular visual odometry using point and line features,

Reference 44

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:35:19.169309Z

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Observation b7e4f13a-87e1-45a1-8800-97c357860be4 · outbound

This paper cites Efficient 3d deep lidar odometry,.

Dense-depth map guided deep Lidar-Visual Odometry with Sparse Point Clouds and Images Efficient 3d deep lidar odometry,

Reference 45

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:35:19.161373Z

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Observation baa1b184-d2d9-4281-a77b-5298aff1cfe0 · outbound

This paper cites Selfvio: Self-supervised deep monocular visual–inertial odometry and depth estimation,.

Dense-depth map guided deep Lidar-Visual Odometry with Sparse Point Clouds and Images Selfvio: Self-supervised deep monocular visual–inertial odometry and depth estimation,

Reference 46

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:35:19.152964Z

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Observation 8d4fc6c4-2ef7-42fe-abcb-eff92a6e5da4 · outbound

This paper cites Un- supervised deep visual-inertial odometry with online error correction for rgb-d imagery,.

Dense-depth map guided deep Lidar-Visual Odometry with Sparse Point Clouds and Images Un- supervised deep visual-inertial odometry with online error correction for rgb-d imagery,

Reference 47

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:35:19.144912Z

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Observation 67c97013-ed81-4b3a-b526-8aed8d6cb542 · outbound

This paper cites Self-supervised depth comple- tion from direct visual-lidar odometry in autonomous driving,.

Dense-depth map guided deep Lidar-Visual Odometry with Sparse Point Clouds and Images Self-supervised depth comple- tion from direct visual-lidar odometry in autonomous driving,

Reference 48

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:35:19.136903Z

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Observation 542e1920-7271-48c0-a863-484d8f2cf69f · outbound

This paper cites Recent advances in conventional and deep learning-based depth completion: A survey,.

Dense-depth map guided deep Lidar-Visual Odometry with Sparse Point Clouds and Images Recent advances in conventional and deep learning-based depth completion: A survey,

Reference 49

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:35:19.128577Z

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This paper cites Multi-sensor fusion self-supervised deep odometry and depth estimation,.

Dense-depth map guided deep Lidar-Visual Odometry with Sparse Point Clouds and Images Multi-sensor fusion self-supervised deep odometry and depth estimation,

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