LaGen: Towards Autoregressive LiDAR Scene Generation | Paper Citation Record

Observation 868e0d8d-90d4-4f1b-b37b-d650134482ed · outbound

This paper cites Deep generative modeling of lidar data.

LaGen: Towards Autoregressive LiDAR Scene Generation Deep generative modeling of lidar data

Reference 1

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Observation ca8b743b-9cd2-409c-968d-db73d54e1025 · outbound

This paper cites nuscenes: A multi- modal dataset for autonomous driving.

LaGen: Towards Autoregressive LiDAR Scene Generation nuscenes: A multi- modal dataset for autonomous driving

Reference 2

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Observation 81447220-9e6e-4a4c-a210-d927280c0fa1 · outbound

This paper cites Diffusion forcing: Next-token prediction meets full-sequence diffu- sion.Advances in Neural Information Processing Systems, 37:24081–24125, 2024.

LaGen: Towards Autoregressive LiDAR Scene Generation Diffusion forcing: Next-token prediction meets full-sequence diffu- sion.Advances in Neural Information Processing Systems, 37:24081–24125, 2024

Reference 3

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Observation 42014308-cfe3-42e6-bdc3-d54e827e6270 · outbound

This paper cites Language-Guided 3D Object Detection in Point Cloud for Autonomous Driving.

LaGen: Towards Autoregressive LiDAR Scene Generation Language-Guided 3D Object Detection in Point Cloud for Autonomous Driving

Reference 4

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Observation 94267b73-8720-4dc0-a6f4-3a07697722bd · outbound

This paper cites Transfuser: Imitation with transformer-based sensor fusion for autonomous driv- ing.IEEE transactions on pattern analysis and machine in- telligence, 45:12878–12895, 2022.

LaGen: Towards Autoregressive LiDAR Scene Generation Transfuser: Imitation with transformer-based sensor fusion for autonomous driv- ing.IEEE transactions on pattern analysis and machine in- telligence, 45:12878–12895, 2022

Reference 5

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Observation 402243c4-36c8-456b-ba35-051c052441ee · outbound

This paper cites Openscene: The largest up-to-date 3d occupancy prediction benchmark in autonomous driv- ing.

LaGen: Towards Autoregressive LiDAR Scene Generation Openscene: The largest up-to-date 3d occupancy prediction benchmark in autonomous driv- ing

Reference 6

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Observation 15478a01-cde0-4c62-bc1e-2152a84090ce · outbound

This paper cites Streetscapes: Large-scale consistent street view generation using autore- gressive video diffusion.

LaGen: Towards Autoregressive LiDAR Scene Generation Streetscapes: Large-scale consistent street view generation using autore- gressive video diffusion

Reference 7

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Observation 8fc305dc-e1e8-44a1-991a-7612cd5b259c · outbound

This paper cites Carla: An open urban driv- ing simulator.

LaGen: Towards Autoregressive LiDAR Scene Generation Carla: An open urban driv- ing simulator

Reference 8

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Observation 345512fc-b9b5-4dc4-9a6d-dc5599f78733 · outbound

This paper cites A point set generation network for 3d object reconstruction from a single image.

LaGen: Towards Autoregressive LiDAR Scene Generation A point set generation network for 3d object reconstruction from a single image

Reference 9

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Observation a559e98d-6ace-4433-841e-33d99642b907 · outbound

This paper cites Vision meets robotics: The KITTI dataset.Inter- national Journal of Robotics Research, 32(11):1231 – 1237,.

LaGen: Towards Autoregressive LiDAR Scene Generation Vision meets robotics: The KITTI dataset.Inter- national Journal of Robotics Research, 32(11):1231 – 1237,

Reference 10

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Observation ff46724b-8f60-4987-ba6e-2acaeb2a9081 · outbound

This paper cites Generative adversarial nets.Advances in neural information processing systems, 27, 2014.

LaGen: Towards Autoregressive LiDAR Scene Generation Generative adversarial nets.Advances in neural information processing systems, 27, 2014

Reference 11

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Observation 06122dae-db57-4f7a-9beb-67c764f5e288 · outbound

This paper cites Vip3d: End-to-end visual trajectory prediction via 3d agent queries.

LaGen: Towards Autoregressive LiDAR Scene Generation Vip3d: End-to-end visual trajectory prediction via 3d agent queries

Reference 12

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Observation 3fbae4c1-87ef-4fb5-90b7-f78460b21695 · outbound

This paper cites Denoising dif- fusion probabilistic models.Advances in neural information processing systems, 33:6840–6851, 2020.

LaGen: Towards Autoregressive LiDAR Scene Generation Denoising dif- fusion probabilistic models.Advances in neural information processing systems, 33:6840–6851, 2020

Reference 13

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Observation e0bb5db0-e33c-4813-9d50-9b9b89d92b6d · outbound

This paper cites Monocular quasi-dense 3d object tracking.IEEE Transactions on Pattern Analysis and Machine Intelligence, 45:1992–2008, 2022.

LaGen: Towards Autoregressive LiDAR Scene Generation Monocular quasi-dense 3d object tracking.IEEE Transactions on Pattern Analysis and Machine Intelligence, 45:1992–2008, 2022

Reference 14

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Observation 12dd720d-ce82-4cf1-8f90-be147046d97f · outbound

This paper cites Rangeldm: Fast realistic lidar point cloud generation.

LaGen: Towards Autoregressive LiDAR Scene Generation Rangeldm: Fast realistic lidar point cloud generation

Reference 15

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Observation d9e7484a-28e3-4448-859e-151334662b61 · outbound

This paper cites St-p3: End-to-end vision-based au- tonomous driving via spatial-temporal feature learning.

LaGen: Towards Autoregressive LiDAR Scene Generation St-p3: End-to-end vision-based au- tonomous driving via spatial-temporal feature learning

Reference 16

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Observation ac32a964-f360-4375-b742-8e60ec9aae94 · outbound

This paper cites Planning-oriented autonomous driving.

LaGen: Towards Autoregressive LiDAR Scene Generation Planning-oriented autonomous driving

Reference 17

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Observation 2f3539b3-1751-4bfb-bfcd-a7a14e727a43 · outbound

This paper cites BEVDet: High-performance Multi-camera 3D Object Detection in Bird-Eye-View.

LaGen: Towards Autoregressive LiDAR Scene Generation BEVDet: High-performance Multi-camera 3D Object Detection in Bird-Eye-View

Reference 18

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Observation 19110f12-dd70-47b2-a824-da47d1c9758a · outbound

This paper cites Bench2drive: Towards multi-ability bench- marking of closed-loop end-to-end autonomous driving.Ad- vances in Neural Information Processing Systems, 37:819– 844, 2024.

LaGen: Towards Autoregressive LiDAR Scene Generation Bench2drive: Towards multi-ability bench- marking of closed-loop end-to-end autonomous driving.Ad- vances in Neural Information Processing Systems, 37:819– 844, 2024

Reference 19

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Observation 5606a897-e9c5-434e-8682-86462a487101 · outbound

This paper cites Vad: Vectorized scene representa- tion for efficient autonomous driving.

LaGen: Towards Autoregressive LiDAR Scene Generation Vad: Vectorized scene representa- tion for efficient autonomous driving

Reference 20

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Observation 361c6741-dba7-4656-a438-b697faf27527 · outbound

This paper cites Towards learning-based planning: 9 The nuplan benchmark for real-world autonomous driving.

LaGen: Towards Autoregressive LiDAR Scene Generation Towards learning-based planning: 9 The nuplan benchmark for real-world autonomous driving

Reference 21

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Observation f65387fd-2b68-4231-b150-c88ae01eafc3 · outbound

This paper cites Point cloud forecasting as a proxy for 4d occupancy forecasting.

LaGen: Towards Autoregressive LiDAR Scene Generation Point cloud forecasting as a proxy for 4d occupancy forecasting

Reference 22

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Observation 4a7823f4-f4f8-420a-bfcb-19ea75bdf567 · outbound

This paper cites Variational diffusion models.Advances in neural infor- mation processing systems, 34:21696–21707, 2021.

LaGen: Towards Autoregressive LiDAR Scene Generation Variational diffusion models.Advances in neural infor- mation processing systems, 34:21696–21707, 2021

Reference 23

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Observation 4229a6a1-3ba0-4846-b0c6-a97d8a9342cc · outbound

This paper cites Auto-Encoding Variational Bayes.

LaGen: Towards Autoregressive LiDAR Scene Generation Auto-Encoding Variational Bayes

Reference 24

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Observation 92628a53-7719-429f-b730-f46c586c6f54 · outbound

This paper cites Lwsis: Lidar-guided weakly supervised instance segmentation for autonomous driving.

LaGen: Towards Autoregressive LiDAR Scene Generation Lwsis: Lidar-guided weakly supervised instance segmentation for autonomous driving

Reference 25

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Observation 45b69bdc-e087-4477-b6e1-99cf534a1880 · outbound

This paper cites Di-v2x: Learning domain- invariant representation for vehicle-infrastructure collabora- tive 3d object detection.

LaGen: Towards Autoregressive LiDAR Scene Generation Di-v2x: Learning domain- invariant representation for vehicle-infrastructure collabora- tive 3d object detection

Reference 26

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Observation 551fe86a-9e23-4824-b685-46f452e01918 · outbound

This paper cites Bevdepth: Acquisition of reliable depth for multi-view 3d object detec- tion.

LaGen: Towards Autoregressive LiDAR Scene Generation Bevdepth: Acquisition of reliable depth for multi-view 3d object detec- tion

Reference 27

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Observation 4bddfeed-446f-463b-aef8-612ae5982342 · outbound

This paper cites End-to-end 3d tracking with decoupled queries.

LaGen: Towards Autoregressive LiDAR Scene Generation End-to-end 3d tracking with decoupled queries

Reference 28

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Observation d13eeffb-5918-4c37-a081-b892c4876e96 · outbound

This paper cites Bevformer: learning bird’s-eye-view representation from lidar-camera via spatiotemporal transformers.IEEE Transactions on Pat- tern Analysis and Machine Intelligence, 2024.

LaGen: Towards Autoregressive LiDAR Scene Generation Bevformer: learning bird’s-eye-view representation from lidar-camera via spatiotemporal transformers.IEEE Transactions on Pat- tern Analysis and Machine Intelligence, 2024

Reference 29

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Observation 20a80a07-bc14-458d-914d-83735b26b86a · outbound

This paper cites Pnpnet: End-to-end per- ception and prediction with tracking in the loop.

LaGen: Towards Autoregressive LiDAR Scene Generation Pnpnet: End-to-end per- ception and prediction with tracking in the loop

Reference 30

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Observation 8df3fa78-9e15-4ece-856f-992e90853f47 · outbound

This paper cites Flownet3d: Learning scene flow in 3d point clouds.

LaGen: Towards Autoregressive LiDAR Scene Generation Flownet3d: Learning scene flow in 3d point clouds

Reference 31

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Observation a13e327f-d431-4679-953d-a316b1c33649 · outbound

This paper cites Pcpnet: An efficient and semantic-enhanced transformer net- work for point cloud prediction.IEEE Robotics and Automa- tion Letters, 8(7):4267–4274, 2023.

LaGen: Towards Autoregressive LiDAR Scene Generation Pcpnet: An efficient and semantic-enhanced transformer net- work for point cloud prediction.IEEE Robotics and Automa- tion Letters, 8(7):4267–4274, 2023

Reference 32

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Observation f7094db7-84e9-43c3-ba42-f0232f394960 · outbound

This paper cites Lidar- only based navigation algorithm for an autonomous agricul- tural robot.Computers and electronics in agriculture, 154: 71–79, 2018.

LaGen: Towards Autoregressive LiDAR Scene Generation Lidar- only based navigation algorithm for an autonomous agricul- tural robot.Computers and electronics in agriculture, 154: 71–79, 2018

Reference 33

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Observation 1c1f69f0-ef86-41a8-9a09-ce6295681714 · outbound

This paper cites Weakly supervised 3d object detection from lidar point cloud.

LaGen: Towards Autoregressive LiDAR Scene Generation Weakly supervised 3d object detection from lidar point cloud

Reference 34

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Observation e473f216-eb9e-4837-8c2d-82023f7d784d · outbound

This paper cites Self-supervised point cloud prediction using 3d spatio-temporal convolutional networks.

LaGen: Towards Autoregressive LiDAR Scene Generation Self-supervised point cloud prediction using 3d spatio-temporal convolutional networks

Reference 35

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Observation 6e35a260-c0e1-4a78-878c-892a39a0fcaf · outbound

This paper cites Lidar data synthe- sis with denoising diffusion probabilistic models.

LaGen: Towards Autoregressive LiDAR Scene Generation Lidar data synthe- sis with denoising diffusion probabilistic models

Reference 36

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Observation 31698e23-df14-4f8b-a9c9-790b932e02f7 · outbound

This paper cites GLIDE: Towards Photorealistic Image Generation and Editing with Text-Guided Diffusion Models.

LaGen: Towards Autoregressive LiDAR Scene Generation GLIDE: Towards Photorealistic Image Generation and Editing with Text-Guided Diffusion Models

Reference 37

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Observation b316ba97-857d-4861-9a01-72cc32ff2ea5 · outbound

This paper cites Improved denoising diffusion probabilistic models.

LaGen: Towards Autoregressive LiDAR Scene Generation Improved denoising diffusion probabilistic models

Reference 38

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Observation 97bfb14f-9476-474c-b792-3a0e887c8348 · outbound

This paper cites Atppnet: Attention based temporal point cloud prediction network.

LaGen: Towards Autoregressive LiDAR Scene Generation Atppnet: Attention based temporal point cloud prediction network

Reference 39

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Observation a3409a76-b771-4dcf-a242-3b738a177420 · outbound

This paper cites Simpletrack: Understanding and rethinking 3d multi-object tracking.

LaGen: Towards Autoregressive LiDAR Scene Generation Simpletrack: Understanding and rethinking 3d multi-object tracking

Reference 40

Resolution: unresolved; no resolver link, observed 2026-08-03T20:05:05.500661Z

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Observation c7d7a056-6404-436d-95c7-6039d9c79c8a · outbound

This paper cites Multi- modal fusion transformer for end-to-end autonomous driv- ing.

LaGen: Towards Autoregressive LiDAR Scene Generation Multi- modal fusion transformer for end-to-end autonomous driv- ing

Reference 41

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Observation c1f68c90-41e1-4115-b939-b2f6b3b4cdc8 · outbound

This paper cites Hierarchical Text-Conditional Image Generation with CLIP Latents.

LaGen: Towards Autoregressive LiDAR Scene Generation Hierarchical Text-Conditional Image Generation with CLIP Latents

Reference 42

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Observation 472595c4-72f9-4535-9326-e22b7a1a34bf · outbound

This paper cites Towards realistic scene generation with lidar diffusion models.

LaGen: Towards Autoregressive LiDAR Scene Generation Towards realistic scene generation with lidar diffusion models

Reference 43

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Observation 264028b2-bd95-426b-a358-40af6f4dfc16 · outbound

This paper cites Drone laser scanning for modeling riverscape topography and vegetation: Comparison with traditional aerial lidar.

LaGen: Towards Autoregressive LiDAR Scene Generation Drone laser scanning for modeling riverscape topography and vegetation: Comparison with traditional aerial lidar

Reference 44

Resolution: unresolved; no resolver link, observed 2026-08-03T20:05:05.510566Z

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Observation ff44b4b3-c9b3-48d6-adaa-eb0602b4fe37 · outbound

This paper cites High-resolution image synthesis with latent diffusion models.

LaGen: Towards Autoregressive LiDAR Scene Generation High-resolution image synthesis with latent diffusion models

Reference 45

Resolution: unresolved; no resolver link, observed 2026-08-03T20:05:05.512845Z

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Observation 38fa28aa-cea8-4994-b6fe-d54a7f54e078 · outbound

This paper cites Photorealistic text-to-image diffusion models with deep language understanding.Advances in neural information processing systems, 35:36479–36494, 2022.

LaGen: Towards Autoregressive LiDAR Scene Generation Photorealistic text-to-image diffusion models with deep language understanding.Advances in neural information processing systems, 35:36479–36494, 2022

Reference 46

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Observation 8fa969a3-4738-4447-ab59-0cc001f0fc01 · outbound

This paper cites Pointr- cnn: 3d object proposal generation and detection from point cloud.

LaGen: Towards Autoregressive LiDAR Scene Generation Pointr- cnn: 3d object proposal generation and detection from point cloud

Reference 47

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Observation f1f791fb-1fc2-46a6-b9e9-3c4dcaed0f27 · outbound

This paper cites Pv-rcnn: Point- voxel feature set abstraction for 3d object detection.

LaGen: Towards Autoregressive LiDAR Scene Generation Pv-rcnn: Point- voxel feature set abstraction for 3d object detection

Reference 48

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Observation aff0b195-cc57-4fc1-8fa8-d3729b3afdb0 · outbound

This paper cites Deep unsupervised learning using nonequilibrium thermodynamics.

LaGen: Towards Autoregressive LiDAR Scene Generation Deep unsupervised learning using nonequilibrium thermodynamics

Reference 49

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Observation 1f2688d0-a671-4625-ad6f-10dbe579d47f · outbound

This paper cites Denoising Diffusion Implicit Models.

LaGen: Towards Autoregressive LiDAR Scene Generation Denoising Diffusion Implicit Models

Reference 50

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Observation 3aee4330-2a10-4b6e-96f6-788cbb1c9307 · outbound

This paper cites Generative modeling by esti- mating gradients of the data distribution.Advances in neural information processing systems, 32, 2019.

LaGen: Towards Autoregressive LiDAR Scene Generation Generative modeling by esti- mating gradients of the data distribution.Advances in neural information processing systems, 32, 2019

Reference 51

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Observation 36785e0a-76f8-497a-9c7c-7bac6f1ab4d8 · outbound

This paper cites Improved techniques for training score-based generative models.Advances in neural information processing systems, 33:12438–12448, 2020.

LaGen: Towards Autoregressive LiDAR Scene Generation Improved techniques for training score-based generative models.Advances in neural information processing systems, 33:12438–12448, 2020

Reference 52

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Observation 10ddf343-e414-4e9b-ada0-f1377dba9211 · outbound

This paper cites Score-Based Generative Modeling through Stochastic Differential Equations.

LaGen: Towards Autoregressive LiDAR Scene Generation Score-Based Generative Modeling through Stochastic Differential Equations

Reference 53

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Observation 923e1245-5fdb-4647-b381-639c1b513cd5 · outbound

This paper cites Scene as occupancy.

LaGen: Towards Autoregressive LiDAR Scene Generation Scene as occupancy

Reference 54

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Observation 26802a6b-cd11-4d0f-9f4a-1ad149751dac · outbound

This paper cites Plant detection and mapping for agricultural robots using a 3d lidar sensor.Robotics and autonomous systems, 59(5):265–273, 2011.

LaGen: Towards Autoregressive LiDAR Scene Generation Plant detection and mapping for agricultural robots using a 3d lidar sensor.Robotics and autonomous systems, 59(5):265–273, 2011

Reference 55

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Observation 0809d8e2-bc31-47a2-8c73-ce82ea7eb2f7 · outbound

This paper cites Inverting the pose forecasting pipeline with spf2: Sequential pointcloud forecasting for se- quential pose forecasting.

LaGen: Towards Autoregressive LiDAR Scene Generation Inverting the pose forecasting pipeline with spf2: Sequential pointcloud forecasting for se- quential pose forecasting

Reference 56

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Observation 9797f69d-7780-46fb-a23f-8f93eda9bf5f · outbound

This paper cites S2net: Stochastic sequential pointcloud forecasting.

LaGen: Towards Autoregressive LiDAR Scene Generation S2net: Stochastic sequential pointcloud forecasting

Reference 57

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Observation 7e6174d8-e7c4-49cd-8e1a-859e4dd3aba4 · outbound

This paper cites Para-drive: Parallelized architecture for real- time autonomous driving.

LaGen: Towards Autoregressive LiDAR Scene Generation Para-drive: Parallelized architecture for real- time autonomous driving

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Observation 5d25f9ad-1189-41a3-a381-bee385e72d4b · outbound

This paper cites Argoverse 2: Next Generation Datasets for Self-Driving Perception and Forecasting.

LaGen: Towards Autoregressive LiDAR Scene Generation Argoverse 2: Next Generation Datasets for Self-Driving Perception and Forecasting

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Resolution: unresolved; no resolver link, observed 2026-08-03T20:05:05.545532Z

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Observation 608c51c0-ecb5-4add-b1ae-39d579ad6c6e · outbound

This paper cites Deep 3d object detection networks using lidar data: A review.IEEE Sensors Journal, 21(2):1152–1171, 2020.

LaGen: Towards Autoregressive LiDAR Scene Generation Deep 3d object detection networks using lidar data: A review.IEEE Sensors Journal, 21(2):1152–1171, 2020

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Resolution: unresolved; no resolver link, observed 2026-08-03T20:05:05.548240Z

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Observation 698a5f9c-32b1-4834-8119-8e8595f8d915 · outbound

This paper cites UltraLiDAR: Learning Compact Representations for LiDAR Completion and Generation.

LaGen: Towards Autoregressive LiDAR Scene Generation UltraLiDAR: Learning Compact Representations for LiDAR Completion and Generation

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Resolution: unresolved; no resolver link, observed 2026-08-03T20:05:05.550571Z

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Observation eaf80d1c-abf5-4f48-92f5-41f3815f0aea · outbound

This paper cites Second: Sparsely embed- ded convolutional detection.Sensors, 18(10), 2018.

LaGen: Towards Autoregressive LiDAR Scene Generation Second: Sparsely embed- ded convolutional detection.Sensors, 18(10), 2018

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Resolution: unresolved; no resolver link, observed 2026-08-03T20:05:05.553062Z

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Observation b0e7abed-5921-494c-a6f4-9da62e77847f · outbound

This paper cites Visual point cloud forecasting enables scalable autonomous driving.

LaGen: Towards Autoregressive LiDAR Scene Generation Visual point cloud forecasting enables scalable autonomous driving

Reference 63

Resolution: unresolved; no resolver link, observed 2026-08-03T20:05:05.555311Z

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Observation 2903afc2-82fc-4133-9c82-cf9304c702cc · outbound

This paper cites Is-fusion: Instance-scene collaborative fusion for multimodal 3d ob- ject detection.

LaGen: Towards Autoregressive LiDAR Scene Generation Is-fusion: Instance-scene collaborative fusion for multimodal 3d ob- ject detection

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Resolution: unresolved; no resolver link, observed 2026-08-03T20:05:05.557732Z

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Observation d923e1a5-d440-4a00-ae5d-d8ccd3b2d969 · outbound

This paper cites Vector-quantized Image Modeling with Improved VQGAN.

LaGen: Towards Autoregressive LiDAR Scene Generation Vector-quantized Image Modeling with Improved VQGAN

Reference 65

Resolution: unresolved; no resolver link, observed 2026-08-03T20:05:05.560196Z

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Observation d5efaa2d-431f-4c91-8ec6-521938d5ec83 · outbound

This paper cites Optical flow and scene flow estimation: A survey.

LaGen: Towards Autoregressive LiDAR Scene Generation Optical flow and scene flow estimation: A survey

Reference 66

Resolution: unresolved; no resolver link, observed 2026-08-03T20:05:05.562749Z

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Observation acf9e411-9811-408a-bc26-61ae7c4c38f8 · outbound

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

LaGen: Towards Autoregressive LiDAR Scene Generation Loam: Lidar odometry and mapping in real-time

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Observation e52089a9-0e13-4554-9fab-2de1426c4b52 · outbound

This paper cites Adding conditional control to text-to-image diffusion models.

LaGen: Towards Autoregressive LiDAR Scene Generation Adding conditional control to text-to-image diffusion models

Reference 68

Resolution: unresolved; no resolver link, observed 2026-08-03T20:05:05.567527Z

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Observation f7404c42-f49b-48f3-b0dc-1ae2f9709f03 · outbound

This paper cites Mutr3d: A multi-camera tracking frame- work via 3d-to-2d queries.

LaGen: Towards Autoregressive LiDAR Scene Generation Mutr3d: A multi-camera tracking frame- work via 3d-to-2d queries

Reference 69

Resolution: unresolved; no resolver link, observed 2026-08-03T20:05:05.569763Z

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Observation d1e5716a-5569-4279-9682-6320ff0fa00c · outbound

This paper cites Learning to generate realistic lidar point clouds.

LaGen: Towards Autoregressive LiDAR Scene Generation Learning to generate realistic lidar point clouds

Reference 70

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