Unposed-to-3D: Learning Simulation-Ready Vehicles from Real-World Images | Paper Citation Record

Observation 787943e3-62bb-40c7-a7f7-9c5705ae60d2 · outbound

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

Unposed-to-3D: Learning Simulation-Ready Vehicles from Real-World Images nuscenes: A multi- modal dataset for autonomous driving

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-05-22T16:21:48.130001Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation b97ba153-7b75-4c56-9853-ad1cb6123c3c · outbound

This paper cites Car full view dataset: Fine-grained predictions of car orientation from images.Electronics, 12(24):4947.

Unposed-to-3D: Learning Simulation-Ready Vehicles from Real-World Images Car full view dataset: Fine-grained predictions of car orientation from images.Electronics, 12(24):4947

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-05-22T16:21:48.109375Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation ccf315a9-9251-4a05-abcb-73c59239f6f7 · outbound

This paper cites ShapeNet: An Information-Rich 3D Model Repository.

Unposed-to-3D: Learning Simulation-Ready Vehicles from Real-World Images ShapeNet: An Information-Rich 3D Model Repository

Reference 3

Resolution: verified exact; arxiv_id, observed 2026-05-11T16:09:06.508173Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 15dc1151-2d4a-4c03-8ea5-e6201a8fb078 · outbound

This paper cites Geosim: Realistic video sim- ulation via geometry-aware composition for self-driving.

Unposed-to-3D: Learning Simulation-Ready Vehicles from Real-World Images Geosim: Realistic video sim- ulation via geometry-aware composition for self-driving

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-05-22T16:21:48.134040Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation c9d6651d-3720-49f0-98e5-7448ee542d65 · outbound

This paper cites Objaverse-xl: A universe of 10m+ 3d objects.Advances in Neural Informa- tion Processing Systems, 36:35799–35813.

Unposed-to-3D: Learning Simulation-Ready Vehicles from Real-World Images Objaverse-xl: A universe of 10m+ 3d objects.Advances in Neural Informa- tion Processing Systems, 36:35799–35813

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-05-22T16:21:48.100186Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation abe38a66-275c-4f14-936d-3b34eb15267b · outbound

This paper cites V oxel r-cnn: Towards high performance voxel-based 3d object detection.

Unposed-to-3D: Learning Simulation-Ready Vehicles from Real-World Images V oxel r-cnn: Towards high performance voxel-based 3d object detection

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-05-22T16:21:48.122828Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 5a1e8c87-60f1-4c3f-85dd-9d4ffdfefcc5 · outbound

This paper cites Dreamcar: Leveraging car-specific prior for in-the-wild 3d car reconstruction.IEEE Robotics and Automation Let- ters.

Unposed-to-3D: Learning Simulation-Ready Vehicles from Real-World Images Dreamcar: Leveraging car-specific prior for in-the-wild 3d car reconstruction.IEEE Robotics and Automation Let- ters

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-05-22T16:21:48.090465Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 796aad36-89be-4498-af32-741fb60f0503 · outbound

This paper cites 3drealcar: An in-the-wild rgb-d car dataset with 360-degree views.

Unposed-to-3D: Learning Simulation-Ready Vehicles from Real-World Images 3drealcar: An in-the-wild rgb-d car dataset with 360-degree views

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-05-22T16:21:48.106019Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 4409f13e-1c81-4c89-adc6-3deb06e8c250 · outbound

This paper cites Get3d: A generative model of high quality 3d tex- tured shapes learned from images.Advances in neural infor- mation processing systems, 35:31841–31854.

Unposed-to-3D: Learning Simulation-Ready Vehicles from Real-World Images Get3d: A generative model of high quality 3d tex- tured shapes learned from images.Advances in neural infor- mation processing systems, 35:31841–31854

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-05-22T16:21:48.057981Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 1184d9b0-4792-49af-9f61-37cee8cb8135 · outbound

This paper cites Tan et al.

Unposed-to-3D: Learning Simulation-Ready Vehicles from Real-World Images Tan et al

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-05-22T16:21:48.083216Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation ee127335-9b53-4df4-a4f3-a07b76605d26 · outbound

This paper cites LRM: Large Reconstruction Model for Single Image to 3D.

Unposed-to-3D: Learning Simulation-Ready Vehicles from Real-World Images LRM: Large Reconstruction Model for Single Image to 3D

Reference 11

Resolution: verified exact; arxiv_id, observed 2026-05-15T10:11:00.998012Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 5c9b3213-0143-4a7b-b77d-a9c283ad04d8 · outbound

This paper cites No pose at all: Self-supervised pose-free 3d gaussian splatting from sparse views.

Unposed-to-3D: Learning Simulation-Ready Vehicles from Real-World Images No pose at all: Self-supervised pose-free 3d gaussian splatting from sparse views

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-05-22T16:21:48.093805Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 94508e21-56d5-4a82-96d6-e00efe6f42d8 · outbound

This paper cites Mvsmamba: Multi-view stereo with state space model.

Unposed-to-3D: Learning Simulation-Ready Vehicles from Real-World Images Mvsmamba: Multi-view stereo with state space model

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-05-22T16:21:48.074281Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 8c63610d-081a-43f1-a1c8-8e66ccdc86b7 · outbound

This paper cites Ultralytics YOLO.

Unposed-to-3D: Learning Simulation-Ready Vehicles from Real-World Images Ultralytics YOLO

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-05-22T16:21:48.103055Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 880c4c6b-8795-4f87-852c-82ec097769bf · outbound

This paper cites Shap-E: Generating Conditional 3D Implicit Functions.

Unposed-to-3D: Learning Simulation-Ready Vehicles from Real-World Images Shap-E: Generating Conditional 3D Implicit Functions

Reference 15

Resolution: verified exact; arxiv_id, observed 2026-05-16T15:32:06.918889Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 14cb8454-9cb5-400f-8653-2edc5c444da4 · outbound

This paper cites Madrive: Memory-augmented driving scene modeling.

Unposed-to-3D: Learning Simulation-Ready Vehicles from Real-World Images Madrive: Memory-augmented driving scene modeling

Reference 16

Resolution: verified exact; arxiv_id, observed 2026-05-11T12:31:03.749983Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 1138c879-1922-4783-adfc-ca2a5325cea6 · outbound

This paper cites Gsnet: Joint vehicle pose and shape recon- struction with geometrical and scene-aware supervision.

Unposed-to-3D: Learning Simulation-Ready Vehicles from Real-World Images Gsnet: Joint vehicle pose and shape recon- struction with geometrical and scene-aware supervision

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-05-22T16:21:48.096934Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 4bc758e5-7984-46f5-8abc-fd9d542a81c0 · outbound

This paper cites 3d gaussian splatting for real-time radiance field rendering.ACM Trans.

Unposed-to-3D: Learning Simulation-Ready Vehicles from Real-World Images 3d gaussian splatting for real-time radiance field rendering.ACM Trans

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-05-22T16:21:48.138330Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 1f916490-7722-4b64-b51b-ac925406fe63 · outbound

This paper cites Habitat synthetic scenes dataset (hssd-200): An analysis of 3d scene scale and realism tradeoffs for objectgoal naviga- tion.

Unposed-to-3D: Learning Simulation-Ready Vehicles from Real-World Images Habitat synthetic scenes dataset (hssd-200): An analysis of 3d scene scale and realism tradeoffs for objectgoal naviga- tion

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-05-22T16:21:48.126298Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation bf580274-f346-4dd8-bcf1-1e6b4dc1ccfb · outbound

This paper cites Instant3D: Fast Text-to-3D with Sparse-View Generation and Large Reconstruction Model.

Unposed-to-3D: Learning Simulation-Ready Vehicles from Real-World Images Instant3D: Fast Text-to-3D with Sparse-View Generation and Large Reconstruction Model

Reference 20

Resolution: verified exact; arxiv_id, observed 2026-05-11T12:31:03.641375Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 08ced50f-5a89-4faa-b870-d6fe540152e3 · outbound

This paper cites Photorealistic object insertion with diffusion-guided inverse rendering.

Unposed-to-3D: Learning Simulation-Ready Vehicles from Real-World Images Photorealistic object insertion with diffusion-guided inverse rendering

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-05-22T16:21:48.060799Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation d5205b8f-0b7e-4207-b147-7dbc01cbad8f · outbound

This paper cites Luciddreamer: Towards high- fidelity text-to-3d generation via interval score matching.

Unposed-to-3D: Learning Simulation-Ready Vehicles from Real-World Images Luciddreamer: Towards high- fidelity text-to-3d generation via interval score matching

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-05-22T16:21:48.077110Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 31e18084-485c-4d1a-af9a-496ad309bae0 · outbound

This paper cites Magic3d: High-resolution text-to-3d content creation.

Unposed-to-3D: Learning Simulation-Ready Vehicles from Real-World Images Magic3d: High-resolution text-to-3d content creation

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-05-22T16:21:48.067765Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation f154b884-69b6-476f-9f69-a47e4463a9d7 · outbound

This paper cites Instdrive: Instance-aware 3d gaussian splatting for driving scenes.

Unposed-to-3D: Learning Simulation-Ready Vehicles from Real-World Images Instdrive: Instance-aware 3d gaussian splatting for driving scenes

Reference 24

Resolution: verified exact; arxiv_id, observed 2026-05-11T12:31:03.632303Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 986e814c-c5d2-4393-88ac-603a0be4f04f · outbound

This paper cites Protocar: Learning 3d vehicle prototypes from single-view and unconstrained driving scene images.

Unposed-to-3D: Learning Simulation-Ready Vehicles from Real-World Images Protocar: Learning 3d vehicle prototypes from single-view and unconstrained driving scene images

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-05-22T16:21:48.144912Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 96e35bd5-12b9-4f25-a2fb-7c713656c237 · outbound

This paper cites One-2-3-45++: Fast single image to 3d objects with consistent multi-view generation and 3d dif- fusion.

Unposed-to-3D: Learning Simulation-Ready Vehicles from Real-World Images One-2-3-45++: Fast single image to 3d objects with consistent multi-view generation and 3d dif- fusion

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-05-22T16:21:48.087311Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 9764334f-96d3-4ca1-aa00-c26079c45a5c · outbound

This paper cites Zero-1-to- 3: Zero-shot one image to 3d object.

Unposed-to-3D: Learning Simulation-Ready Vehicles from Real-World Images Zero-1-to- 3: Zero-shot one image to 3d object

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-05-22T16:21:48.064236Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 4d6e403b-e53f-444c-bf98-b3795b4666c7 · outbound

This paper cites Car-studio: learning car radiance fields from single- view and unlimited in-the-wild images.IEEE Robotics and Automation Letters, 9(3).

Unposed-to-3D: Learning Simulation-Ready Vehicles from Real-World Images Car-studio: learning car radiance fields from single- view and unlimited in-the-wild images.IEEE Robotics and Automation Letters, 9(3)

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-05-22T16:21:48.071114Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 20effcb4-bd84-4a65-81b4-d32f4e172460 · outbound

This paper cites R3D2: Realistic 3D Asset Insertion via Diffusion for Autonomous Driving Simulation.

Unposed-to-3D: Learning Simulation-Ready Vehicles from Real-World Images R3D2: Realistic 3D Asset Insertion via Diffusion for Autonomous Driving Simulation

Reference 29

Resolution: verified exact; local_arxiv, observed 2026-05-11T12:31:03.817355Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation fcec082f-5285-4c59-a6aa-8f5d08fd88f2 · outbound

This paper cites Ur- bancad: Towards highly controllable and photorealistic 3d vehicles for urban scene simulation.

Unposed-to-3D: Learning Simulation-Ready Vehicles from Real-World Images Ur- bancad: Towards highly controllable and photorealistic 3d vehicles for urban scene simulation

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-05-22T16:21:48.116250Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 80d8fe9e-a80e-491f-ad32-cf3d41e822a4 · outbound

This paper cites Nerf: Representing scenes as neural radiance fields for view syn- thesis.Communications of the ACM, 65(1):99–106.

Unposed-to-3D: Learning Simulation-Ready Vehicles from Real-World Images Nerf: Representing scenes as neural radiance fields for view syn- thesis.Communications of the ACM, 65(1):99–106

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-05-22T16:21:48.113024Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 927badf3-2b3c-42eb-b544-a0cc86b174a1 · outbound

This paper cites 3d bounding box estimation using deep learn- ing and geometry.

Unposed-to-3D: Learning Simulation-Ready Vehicles from Real-World Images 3d bounding box estimation using deep learn- ing and geometry

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-05-22T16:21:48.141819Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation d8ee4556-07b0-4e9b-9a7c-ee97e1340430 · outbound

This paper cites Autorf: Learning 3d object radiance fields from single view observations.

Unposed-to-3D: Learning Simulation-Ready Vehicles from Real-World Images Autorf: Learning 3d object radiance fields from single view observations

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-05-22T16:21:48.080223Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 2cc04241-781f-4692-9045-92159b8c967b · outbound

This paper cites Point-E: A System for Generating 3D Point Clouds from Complex Prompts.

Unposed-to-3D: Learning Simulation-Ready Vehicles from Real-World Images Point-E: A System for Generating 3D Point Clouds from Complex Prompts

Reference 34

Resolution: verified exact; arxiv_id, observed 2026-05-14T20:51:35.400576Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 24bf27f1-4d88-4f65-9eda-58028cb733ba · outbound

This paper cites DINOv2: Learning Robust Visual Features without Supervision.

Unposed-to-3D: Learning Simulation-Ready Vehicles from Real-World Images DINOv2: Learning Robust Visual Features without Supervision

Reference 35

Resolution: verified exact; local_arxiv, observed 2026-05-11T12:31:03.793117Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 509cf385-2a4c-4d45-95df-17a0969c35b1 · outbound

This paper cites Neural scene graphs for dynamic scenes.

Unposed-to-3D: Learning Simulation-Ready Vehicles from Real-World Images Neural scene graphs for dynamic scenes

Reference 36

Resolution: verified fuzzy; raw_fallback, observed 2026-05-22T16:21:48.119403Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation a20d5587-a51f-4173-8c26-4d8262cc347c · outbound

This paper cites One-Step Image Translation with Text-to-Image Models.

Unposed-to-3D: Learning Simulation-Ready Vehicles from Real-World Images One-Step Image Translation with Text-to-Image Models

Reference 37

Resolution: verified exact; arxiv_id, observed 2026-05-11T12:31:03.691538Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 56a36336-85b0-415b-90dc-998957e6da6c · outbound

This paper cites Scalable diffusion models with transformers.

Unposed-to-3D: Learning Simulation-Ready Vehicles from Real-World Images Scalable diffusion models with transformers

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-05-22T16:21:48.154929Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation c419988e-fd0d-40c7-b424-a5f318d06da9 · outbound

This paper cites DreamFusion: Text-to-3D using 2D Diffusion.

Unposed-to-3D: Learning Simulation-Ready Vehicles from Real-World Images DreamFusion: Text-to-3D using 2D Diffusion

Reference 39

Resolution: verified exact; local_arxiv, observed 2026-05-11T12:31:03.682941Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 20f9b398-641e-46d9-af55-41cf303c9981 · outbound

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

Unposed-to-3D: Learning Simulation-Ready Vehicles from Real-World Images High-resolution image synthesis with latent diffusion models

Reference 40

Resolution: verified fuzzy; raw_fallback, observed 2026-05-22T16:21:48.158655Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 4c5486fc-d0ae-4b25-a89d-5f7c8f379b1f · outbound

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

Unposed-to-3D: Learning Simulation-Ready Vehicles from Real-World Images Photorealistic text-to-image diffusion models with deep language understanding.Advances in neural information processing systems, 35:36479–36494

Reference 41

Resolution: verified fuzzy; raw_fallback, observed 2026-05-22T16:21:48.168840Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 8a73018c-7345-4180-bbf0-dd7c59df96cb · outbound

This paper cites Structure- from-motion revisited.

Unposed-to-3D: Learning Simulation-Ready Vehicles from Real-World Images Structure- from-motion revisited

Reference 42

Resolution: verified fuzzy; raw_fallback, observed 2026-05-22T16:21:48.222804Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 3c4eadaf-31d3-4761-a980-793254e7f60c · outbound

This paper cites Gina-3d: Learning to generate implicit neural assets in the wild.

Unposed-to-3D: Learning Simulation-Ready Vehicles from Real-World Images Gina-3d: Learning to generate implicit neural assets in the wild

Reference 43

Resolution: verified fuzzy; raw_fallback, observed 2026-05-22T16:21:48.151463Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 3a19d972-89c4-402b-885c-23c32c342880 · outbound

This paper cites Scalability in perception for autonomous driving: Waymo open dataset.

Unposed-to-3D: Learning Simulation-Ready Vehicles from Real-World Images Scalability in perception for autonomous driving: Waymo open dataset

Reference 44

Resolution: verified fuzzy; raw_fallback, observed 2026-05-22T16:21:48.208444Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation ecc21263-9959-426d-aef8-dd5c2bc32b99 · outbound

This paper cites DreamGaussian: Generative Gaussian Splatting for Efficient 3D Content Creation.

Unposed-to-3D: Learning Simulation-Ready Vehicles from Real-World Images DreamGaussian: Generative Gaussian Splatting for Efficient 3D Content Creation

Reference 45

Resolution: verified exact; arxiv_id, observed 2026-05-16T10:18:06.729150Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 01443283-2717-4446-999a-a97ce9c83f65 · outbound

This paper cites Lgm: Large multi-view gaussian model for high-resolution 3d content creation.

Unposed-to-3D: Learning Simulation-Ready Vehicles from Real-World Images Lgm: Large multi-view gaussian model for high-resolution 3d content creation

Reference 46

Resolution: verified fuzzy; raw_fallback, observed 2026-05-22T16:21:48.165018Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation bf0f7c19-fbfc-4873-8b4b-b2aa539a3d44 · outbound

This paper cites Openpcdet: An open- source toolbox for 3d object detection from point clouds.

Unposed-to-3D: Learning Simulation-Ready Vehicles from Real-World Images Openpcdet: An open- source toolbox for 3d object detection from point clouds

Reference 47

Resolution: verified fuzzy; raw_fallback, observed 2026-05-22T16:21:48.219214Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation db4c84cc-210a-45e0-9242-d022d3af1d99 · outbound

This paper cites CADSim: Robust and Scalable in-the-wild 3D Reconstruction for Controllable Sensor Simulation.

Unposed-to-3D: Learning Simulation-Ready Vehicles from Real-World Images CADSim: Robust and Scalable in-the-wild 3D Reconstruction for Controllable Sensor Simulation

Reference 48

Resolution: verified exact; arxiv_id, observed 2026-05-11T12:31:03.664923Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 8adc5381-2fcc-43b8-835c-316f86987e60 · outbound

This paper cites Vggsfm: Visual geometry grounded deep structure from motion.

Unposed-to-3D: Learning Simulation-Ready Vehicles from Real-World Images Vggsfm: Visual geometry grounded deep structure from motion

Reference 49

Resolution: verified fuzzy; raw_fallback, observed 2026-05-22T16:21:48.225905Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 4091c57a-ff7f-420b-b735-7c02fc73db76 · outbound

This paper cites Vggt: Vi- sual geometry grounded transformer.

Unposed-to-3D: Learning Simulation-Ready Vehicles from Real-World Images Vggt: Vi- sual geometry grounded transformer

Reference 50

Resolution: verified fuzzy; raw_fallback, observed 2026-05-22T16:21:48.162033Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 7a17b5bd-ff0c-46a4-a63d-4484c7219c71 · outbound

This paper cites Dust3r: Geometric 3d vi- sion made easy.

Unposed-to-3D: Learning Simulation-Ready Vehicles from Real-World Images Dust3r: Geometric 3d vi- sion made easy

Reference 51

Resolution: verified fuzzy; raw_fallback, observed 2026-05-22T16:21:48.205062Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 051a9e6b-23f5-427f-92eb-5ab399b2df26 · outbound

This paper cites Prolificdreamer: High-fidelity and diverse text-to-3d generation with variational score distilla- tion.Advances in neural information processing systems, 36: 8406–8441.

Unposed-to-3D: Learning Simulation-Ready Vehicles from Real-World Images Prolificdreamer: High-fidelity and diverse text-to-3d generation with variational score distilla- tion.Advances in neural information processing systems, 36: 8406–8441

Reference 52

Resolution: verified fuzzy; raw_fallback, observed 2026-05-22T16:21:48.229993Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 99458766-5d70-459f-a79a-c5c61555bf04 · outbound

This paper cites Orient Anything: Learning Robust Object Orientation Estimation from Rendering 3D Models.

Unposed-to-3D: Learning Simulation-Ready Vehicles from Real-World Images Orient Anything: Learning Robust Object Orientation Estimation from Rendering 3D Models

Reference 53

Resolution: verified exact; arxiv_id, observed 2026-05-11T12:31:03.722254Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation b50f2af5-e8de-4319-a7a2-83847673e83f · outbound

This paper cites Dycrowd: Towards dynamic crowd reconstruction from a large-scene video.IEEE Transactions on Pattern Analysis and Machine Intelligence.

Unposed-to-3D: Learning Simulation-Ready Vehicles from Real-World Images Dycrowd: Towards dynamic crowd reconstruction from a large-scene video.IEEE Transactions on Pattern Analysis and Machine Intelligence

Reference 54

Resolution: verified fuzzy; raw_fallback, observed 2026-05-22T16:21:48.233692Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation b16b1f0d-c1cd-4e8b-a9fa-b8505233647e · outbound

This paper cites Mars: An instance-aware, mod- ular and realistic simulator for autonomous driving.

Unposed-to-3D: Learning Simulation-Ready Vehicles from Real-World Images Mars: An instance-aware, mod- ular and realistic simulator for autonomous driving

Reference 55

Resolution: verified fuzzy; raw_fallback, observed 2026-05-22T16:21:48.191160Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation f8b0514a-7472-4ca8-b539-45cfee628629 · outbound

This paper cites Structured 3d latents for scalable and versatile 3d gen- eration.

Unposed-to-3D: Learning Simulation-Ready Vehicles from Real-World Images Structured 3d latents for scalable and versatile 3d gen- eration

Reference 56

Resolution: verified fuzzy; raw_fallback, observed 2026-05-22T16:21:48.215365Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation e5d59582-c26b-4a74-a60e-e68c02c72581 · outbound

This paper cites Data-driven 3d voxel patterns for object category recogni- tion.

Unposed-to-3D: Learning Simulation-Ready Vehicles from Real-World Images Data-driven 3d voxel patterns for object category recogni- tion

Reference 57

Resolution: verified fuzzy; raw_fallback, observed 2026-05-22T16:21:48.194588Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 9b89da43-b25e-4844-a49e-fca8ce87e0d2 · outbound

This paper cites Pandaset: Advanced sensor suite dataset for autonomous driving.

Unposed-to-3D: Learning Simulation-Ready Vehicles from Real-World Images Pandaset: Advanced sensor suite dataset for autonomous driving

Reference 58

Resolution: verified fuzzy; raw_fallback, observed 2026-05-22T16:21:48.187470Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 9ac34841-17f9-4dd3-b16c-13d25c633423 · outbound

This paper cites InstantMesh: Efficient 3D Mesh Generation from a Single Image with Sparse-view Large Reconstruction Models.

Unposed-to-3D: Learning Simulation-Ready Vehicles from Real-World Images InstantMesh: Efficient 3D Mesh Generation from a Single Image with Sparse-view Large Reconstruction Models

Reference 59

Resolution: verified exact; arxiv_id, observed 2026-05-13T21:15:33.601715Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation b0ecaa5c-ece8-481d-aa8b-5aaf4e63098c · outbound

This paper cites Street gaussians: Modeling dynamic urban scenes with gaussian splatting.

Unposed-to-3D: Learning Simulation-Ready Vehicles from Real-World Images Street gaussians: Modeling dynamic urban scenes with gaussian splatting

Reference 60

Resolution: verified fuzzy; raw_fallback, observed 2026-05-22T16:21:48.183826Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation c80a4071-86b1-4878-8907-33894938f517 · outbound

This paper cites Unisim: A neural closed-loop sensor simulator.

Unposed-to-3D: Learning Simulation-Ready Vehicles from Real-World Images Unisim: A neural closed-loop sensor simulator

Reference 61

Resolution: verified fuzzy; raw_fallback, observed 2026-05-22T16:21:48.148252Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 1bb31796-ef93-4f88-ab79-1f6c47faf8eb · outbound

This paper cites Get3dgs: Generate 3d gaussians based on points deformation fields.IEEE Transactions on Circuits and Systems for Video Technology.

Unposed-to-3D: Learning Simulation-Ready Vehicles from Real-World Images Get3dgs: Generate 3d gaussians based on points deformation fields.IEEE Transactions on Circuits and Systems for Video Technology

Reference 62

Resolution: verified fuzzy; raw_fallback, observed 2026-05-22T16:21:48.176274Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 780c735c-2c37-4460-ad57-cf82cd871aad · outbound

This paper cites Xyzcylinder: Towards compatible feed-forward 3d gaussian splatting for driving scenes via unified cylinder lifting method.

Unposed-to-3D: Learning Simulation-Ready Vehicles from Real-World Images Xyzcylinder: Towards compatible feed-forward 3d gaussian splatting for driving scenes via unified cylinder lifting method

Reference 63

Resolution: verified exact; arxiv_id, observed 2026-05-11T12:31:03.709812Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 3459ec34-4a5e-42bf-bb78-c053973ca3e0 · outbound

This paper cites Faster Segment Anything: Towards Lightweight SAM for Mobile Applications.

Unposed-to-3D: Learning Simulation-Ready Vehicles from Real-World Images Faster Segment Anything: Towards Lightweight SAM for Mobile Applications

Reference 64

Resolution: verified exact; arxiv_id, observed 2026-05-17T22:41:43.533652Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation fdc7bd95-3a7b-4582-b2c1-20b6dd8e25b4 · outbound

This paper cites Hugsim: A real-time, photo-realistic and closed-loop simulator for autonomous driving.IEEE Trans- actions on Pattern Analysis and Machine Intelligence.

Unposed-to-3D: Learning Simulation-Ready Vehicles from Real-World Images Hugsim: A real-time, photo-realistic and closed-loop simulator for autonomous driving.IEEE Trans- actions on Pattern Analysis and Machine Intelligence

Reference 65

Resolution: verified fuzzy; raw_fallback, observed 2026-05-22T16:21:48.212247Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 839c0156-5ecf-4973-a05d-a95a7d7278c2 · outbound

This paper cites Triplane meets gaussian splatting: Fast and generalizable single-view 3d reconstruction with transformers.

Unposed-to-3D: Learning Simulation-Ready Vehicles from Real-World Images Triplane meets gaussian splatting: Fast and generalizable single-view 3d reconstruction with transformers

Reference 66

Resolution: verified fuzzy; raw_fallback, observed 2026-05-22T16:21:48.172292Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation b0ce5632-f4c3-4d14-ada3-f724f3624376 · outbound

This paper cites Network Architectures Texture Block cross self mlp zpatch𝑃𝑃 𝑃𝑃 𝑃𝑃 Geometry Block cross self mlp zcls × 5 × 10 Figure 5.

Unposed-to-3D: Learning Simulation-Ready Vehicles from Real-World Images Network Architectures Texture Block cross self mlp zpatch𝑃𝑃 𝑃𝑃 𝑃𝑃 Geometry Block cross self mlp zcls × 5 × 10 Figure 5

Reference 67

Resolution: verified fuzzy; raw_fallback, observed 2026-05-22T16:21:48.197981Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 63709105-6a11-4476-8029-e63e60e493fb · outbound

This paper cites an unresolved cited work.

Unposed-to-3D: Learning Simulation-Ready Vehicles from Real-World Images Unresolved cited work

Reference 68

Resolution: unresolved; raw_fallback, observed 2026-05-22T16:21:48.180007Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 5cad0c42-cdd6-476f-b52c-2ebd09f09bcd · outbound

This paper cites In addition we do not explic- itly model shadows cast by environmental illumination.

Unposed-to-3D: Learning Simulation-Ready Vehicles from Real-World Images In addition we do not explic- itly model shadows cast by environmental illumination

Reference 69

Resolution: verified fuzzy; raw_fallback, observed 2026-05-22T16:21:48.201493Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

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Reference resolution

Outbound references

Pith citing papers