MObI: Multimodal Object Inpainting Using Diffusion Models | Paper Citation Record

Observation 1ceea53d-45f1-43e7-9547-1a34f25c7fa8 · outbound

This paper cites Flamingo: a visual language model for few-shot learning.

MObI: Multimodal Object Inpainting Using Diffusion Models Flamingo: a visual language model for few-shot learning

Reference 1

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Observation f4abcf9c-9d23-4c5b-b5c3-5d1c2a1a0c9f · outbound

This paper cites Dynamiccity: Large-scale lidar gener- ation from dynamic scenes, 2024.

MObI: Multimodal Object Inpainting Using Diffusion Models Dynamiccity: Large-scale lidar gener- ation from dynamic scenes, 2024

Reference 2

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Observation fb35b2a9-aae3-4e8b-800a-a074fb36f1a1 · outbound

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

MObI: Multimodal Object Inpainting Using Diffusion Models nuscenes: A multi- modal dataset for autonomous driving

Reference 3

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Observation 3ec9a4be-7981-4aed-aa8c-fd2c93cab1de · outbound

This paper cites Just Add $100 More: Augmenting NeRF-based Pseudo-LiDAR Point Cloud for Resolving Class-imbalance Problem.

MObI: Multimodal Object Inpainting Using Diffusion Models Just Add $100 More: Augmenting NeRF-based Pseudo-LiDAR Point Cloud for Resolving Class-imbalance Problem

Reference 4

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Observation 31a25eec-0050-4a4e-9db4-e487a5f2f5de · outbound

This paper cites AnyDoor: Zero-shot Object-level Image Customization.

MObI: Multimodal Object Inpainting Using Diffusion Models AnyDoor: Zero-shot Object-level Image Customization

Reference 5

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Observation e201e549-1cf1-4e75-b3f0-fe1a1fdbd46c · outbound

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

MObI: Multimodal Object Inpainting Using Diffusion Models Geosim: Realistic video sim- ulation via geometry-aware composition for self-driving

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:56:18.920739Z

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Observation 8ad4d6d2-fcae-4603-a6b5-7852b415057d · outbound

This paper cites Placing Objects in Context via Inpainting for Out-of-distribution Segmentation.

MObI: Multimodal Object Inpainting Using Diffusion Models Placing Objects in Context via Inpainting for Out-of-distribution Segmentation

Reference 7

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Observation 8f35d35b-3f7f-490e-ae88-b43183191bf1 · outbound

This paper cites Cut, paste and learn: Surprisingly easy synthesis for instance de- tection.

MObI: Multimodal Object Inpainting Using Diffusion Models Cut, paste and learn: Surprisingly easy synthesis for instance de- tection

Reference 8

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Observation ec0dc077-5d3e-4b17-9400-1b2ac12adfd2 · outbound

This paper cites Taming transformers for high-resolution image synthesis.

MObI: Multimodal Object Inpainting Using Diffusion Models Taming transformers for high-resolution image synthesis

Reference 9

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Observation 4a2d0f31-e302-4ae8-9474-f05098c7a7d3 · outbound

This paper cites MagicDrive: Street View Generation with Diverse 3D Geometry Control.

MObI: Multimodal Object Inpainting Using Diffusion Models MagicDrive: Street View Generation with Diverse 3D Geometry Control

Reference 10

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Observation 30eb62cf-3d8e-4c71-a58c-5b2e5a22511e · outbound

This paper cites Multitest: Physical-aware object insertion for testing multi-sensor fusion perception systems.

MObI: Multimodal Object Inpainting Using Diffusion Models Multitest: Physical-aware object insertion for testing multi-sensor fusion perception systems

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:56:18.878466Z

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Observation 92d1b274-6a43-4751-ade1-031c7dccfe12 · outbound

This paper cites Synthesizing Training Data for Object Detection in Indoor Scenes.

MObI: Multimodal Object Inpainting Using Diffusion Models Synthesizing Training Data for Object Detection in Indoor Scenes

Reference 12

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Observation 8c3a3708-31af-4e60-805a-ccac02f07346 · outbound

This paper cites Sim- ple copy-paste is a strong data augmentation method for in- stance segmentation.

MObI: Multimodal Object Inpainting Using Diffusion Models Sim- ple copy-paste is a strong data augmentation method for in- stance segmentation

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:56:18.862232Z

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Observation d65d071e-b193-48e9-ae1e-737705f845f8 · outbound

This paper cites Generative adversarial nets.

MObI: Multimodal Object Inpainting Using Diffusion Models Generative adversarial nets

Reference 14

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Observation 3ad0f58f-248b-490b-94a0-b992e527141e · outbound

This paper cites Lift-attend-splat: Bird’s-eye-view camera-lidar fusion using transformers, 2024.

MObI: Multimodal Object Inpainting Using Diffusion Models Lift-attend-splat: Bird’s-eye-view camera-lidar fusion using transformers, 2024

Reference 15

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Observation ea9c71a9-1651-4e93-a135-1f6b7c18751e · outbound

This paper cites Gans trained by a two time-scale update rule converge to a local nash equilib- rium.

MObI: Multimodal Object Inpainting Using Diffusion Models Gans trained by a two time-scale update rule converge to a local nash equilib- rium

Reference 16

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Observation 983f6922-7551-43d9-9ae9-d78abcdf0186 · outbound

This paper cites Classifier-Free Diffusion Guidance.

MObI: Multimodal Object Inpainting Using Diffusion Models Classifier-Free Diffusion Guidance

Reference 17

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Observation 37b2e307-75ba-444d-8961-ed5250f7f0c7 · outbound

This paper cites Denoising dif- fusion probabilistic models.

MObI: Multimodal Object Inpainting Using Diffusion Models Denoising dif- fusion probabilistic models

Reference 18

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Observation 436074c9-675a-4c56-b87e-7b7892636228 · outbound

This paper cites Rangeldm: Fast realistic lidar point cloud generation, 2024.

MObI: Multimodal Object Inpainting Using Diffusion Models Rangeldm: Fast realistic lidar point cloud generation, 2024

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:56:18.799535Z

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Observation ed158624-8ff3-4fef-9e97-029e44d57853 · outbound

This paper cites Subjectdrive: Scaling generative data in autonomous driving via subject control, 2024.

MObI: Multimodal Object Inpainting Using Diffusion Models Subjectdrive: Scaling generative data in autonomous driving via subject control, 2024

Reference 20

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Observation b3bb0344-3905-4d37-9ecb-04d4dc72dd0a · outbound

This paper cites Auto-Encoding Variational Bayes.

MObI: Multimodal Object Inpainting Using Diffusion Models Auto-Encoding Variational Bayes

Reference 21

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Observation 6d0a0da8-d37c-49eb-b21e-6953b82b0639 · outbound

This paper cites Logen: Toward lidar object generation by point dif- fusion.

MObI: Multimodal Object Inpainting Using Diffusion Models Logen: Toward lidar object generation by point dif- fusion

Reference 22

Resolution: verified exact; raw_fallback, observed 2026-08-10T21:56:18.096220Z

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Observation 469240ef-56a3-4c90-a5d3-0b3fc5e762ac · outbound

This paper cites Segment Anything.

MObI: Multimodal Object Inpainting Using Diffusion Models Segment Anything

Reference 23

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Observation ce39912a-5252-4f2b-8467-5745d75a6a81 · outbound

This paper cites Challenges in au- tonomous vehicle testing and validation.

MObI: Multimodal Object Inpainting Using Diffusion Models Challenges in au- tonomous vehicle testing and validation

Reference 24

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Observation 57ba7a44-af7f-4f18-864f-492a9073bcfb · outbound

This paper cites Efros, and Krishna Kumar Singh.

MObI: Multimodal Object Inpainting Using Diffusion Models Efros, and Krishna Kumar Singh

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:56:18.750128Z

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Observation 305a4560-28a1-47e8-9f8d-6fd3348fcea6 · outbound

This paper cites Lift3d: Synthesize 3d training data by lift- ing 2d gan to 3d generative radiance field.

MObI: Multimodal Object Inpainting Using Diffusion Models Lift3d: Synthesize 3d training data by lift- ing 2d gan to 3d generative radiance field

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:56:18.734014Z

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Observation 0c6e2faf-b88d-48fc-85af-79861b4d160e · outbound

This paper cites DrivingDiffusion: Layout-Guided multi-view driving scene video generation with latent diffusion model.

MObI: Multimodal Object Inpainting Using Diffusion Models DrivingDiffusion: Layout-Guided multi-view driving scene video generation with latent diffusion model

Reference 27

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Observation 1b1ec102-21be-4c96-8731-f664d3ade34e · outbound

This paper cites Exploring geometric consistency for monocular 3d object detection.

MObI: Multimodal Object Inpainting Using Diffusion Models Exploring geometric consistency for monocular 3d object detection

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:56:18.718662Z

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Observation 8cba1310-bb21-4f93-96b8-83092fb11df3 · outbound

This paper cites Bevfusion: A simple and robust lidar-camera fusion framework, 2022.

MObI: Multimodal Object Inpainting Using Diffusion Models Bevfusion: A simple and robust lidar-camera fusion framework, 2022

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:56:18.703286Z

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Observation bd5ac471-f523-4d4e-a305-bd178c5025ca · outbound

This paper cites Drive-1-to-3: Enriching Diffusion Priors for Novel View Synthesis of Real Vehicles.

MObI: Multimodal Object Inpainting Using Diffusion Models Drive-1-to-3: Enriching Diffusion Priors for Novel View Synthesis of Real Vehicles

Reference 30

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Observation 4534147c-cd8d-4643-ae89-6b68568a61f3 · outbound

This paper cites St-gan: Spatial transformer generative adversarial networks for image compositing.

MObI: Multimodal Object Inpainting Using Diffusion Models St-gan: Spatial transformer generative adversarial networks for image compositing

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:56:18.687570Z

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Observation c4a100ad-469f-47bd-8c4d-59c2b2b75c05 · outbound

This paper cites Pseudo Numerical Methods for Diffusion Models on Manifolds.

MObI: Multimodal Object Inpainting Using Diffusion Models Pseudo Numerical Methods for Diffusion Models on Manifolds

Reference 32

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Observation 5cc4de9a-98f5-477b-9760-a1dbc497e3e0 · outbound

This paper cites Swin transformer: Hierarchical vision transformer using shifted windows.

MObI: Multimodal Object Inpainting Using Diffusion Models Swin transformer: Hierarchical vision transformer using shifted windows

Reference 33

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Observation 947cbaf7-2362-426e-be74-cc04beb84f60 · outbound

This paper cites Bevfusion: Multi- task multi-sensor fusion with unified bird’s-eye view repre- sentation.

MObI: Multimodal Object Inpainting Using Diffusion Models Bevfusion: Multi- task multi-sensor fusion with unified bird’s-eye view repre- sentation

Reference 34

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Observation eb6f9c65-cd49-431c-93d1-e6f4b1af338f · outbound

This paper cites Wovogen: World volume-aware diffusion for con- trollable multi-camera driving scene generation.

MObI: Multimodal Object Inpainting Using Diffusion Models Wovogen: World volume-aware diffusion for con- trollable multi-camera driving scene generation

Reference 35

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:56:18.643099Z

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Observation 330b05a6-59ac-4f91-bc63-8efbfdb0bec9 · outbound

This paper cites Object 3dit: Language-guided 3d-aware image editing.

MObI: Multimodal Object Inpainting Using Diffusion Models Object 3dit: Language-guided 3d-aware image editing

Reference 36

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Observation fafdc0b9-2a18-4561-a9e1-f6b40e99318d · outbound

This paper cites Simple open-vocabulary object detection.

MObI: Multimodal Object Inpainting Using Diffusion Models Simple open-vocabulary object detection

Reference 37

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Observation 53f19588-67f1-4955-ac9b-25a2b6aeee54 · outbound

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

MObI: Multimodal Object Inpainting Using Diffusion Models Lidar data synthe- sis with denoising diffusion probabilistic models

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:56:18.594970Z

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Observation c97af81a-6df5-44d2-8414-c288a6e09f4b · outbound

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

MObI: Multimodal Object Inpainting Using Diffusion Models DINOv2: Learning Robust Visual Features without Supervision

Reference 39

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Observation f3004938-7190-4940-b9f2-aa7548a7cfea · outbound

This paper cites Diffusion handles enabling 3d edits for diffusion models by lifting ac- tivations to 3d.

MObI: Multimodal Object Inpainting Using Diffusion Models Diffusion handles enabling 3d edits for diffusion models by lifting ac- tivations to 3d

Reference 40

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:56:18.579070Z

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Observation 2a8a809b-dd46-4af4-bcec-c7e84c6a3953 · outbound

This paper cites Learning transferable visual models from natural language supervi- sion.

MObI: Multimodal Object Inpainting Using Diffusion Models Learning transferable visual models from natural language supervi- sion

Reference 41

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Observation d7455579-c92b-463d-b441-42ff75dd0ba9 · outbound

This paper cites Towards realistic scene generation with lidar diffusion models, 2024.

MObI: Multimodal Object Inpainting Using Diffusion Models Towards realistic scene generation with lidar diffusion models, 2024

Reference 42

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:56:18.552088Z

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Observation beecb48a-36d5-4b79-a2f4-c45bb384afcf · outbound

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

MObI: Multimodal Object Inpainting Using Diffusion Models High-resolution image synthesis with latent diffusion models

Reference 43

Resolution: unresolved; no resolver link, observed 2026-08-10T21:56:17.568755Z

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Observation 90dabf68-a43d-4733-a263-333de67b95c9 · outbound

This paper cites U- net: Convolutional networks for biomedical image segmen- tation.

MObI: Multimodal Object Inpainting Using Diffusion Models U- net: Convolutional networks for biomedical image segmen- tation

Reference 44

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:56:18.523057Z

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Observation 222f795f-7ebd-4a5f-8140-c38329b3e780 · outbound

This paper cites Dreambooth: Fine tuning text-to-image diffusion models for subject-driven generation.

MObI: Multimodal Object Inpainting Using Diffusion Models Dreambooth: Fine tuning text-to-image diffusion models for subject-driven generation

Reference 45

Resolution: unresolved; no resolver link, observed 2026-08-10T21:56:17.578145Z

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Observation 7b9346af-f29a-4326-9a0c-1e3cf40e6e7f · outbound

This paper cites Jacobs, and Shlomi Fruchter.

MObI: Multimodal Object Inpainting Using Diffusion Models Jacobs, and Shlomi Fruchter

Reference 46

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:56:18.496931Z

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Observation 37a1e6ee-553c-432b-8264-148279880619 · outbound

This paper cites GenMM: Geometrically and Temporally Consistent Multimodal Data Generation for Video and LiDAR.

MObI: Multimodal Object Inpainting Using Diffusion Models GenMM: Geometrically and Temporally Consistent Multimodal Data Generation for Video and LiDAR

Reference 47

Resolution: unresolved; no resolver link, observed 2026-08-10T21:56:17.587143Z

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Observation 7ef3ab6c-4993-4be2-98bd-f9fdd66848c1 · outbound

This paper cites Deep unsupervised learning using nonequilibrium thermodynamics.

MObI: Multimodal Object Inpainting Using Diffusion Models Deep unsupervised learning using nonequilibrium thermodynamics

Reference 48

Resolution: unresolved; no resolver link, observed 2026-08-10T21:56:17.592439Z

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Observation 568ec495-6ffc-4b02-af33-562f1e8a35c5 · outbound

This paper cites Object- stitch: Object compositing with diffusion model.

MObI: Multimodal Object Inpainting Using Diffusion Models Object- stitch: Object compositing with diffusion model

Reference 49

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:56:18.470970Z

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Observation a0e115f2-baca-4447-ae38-1fe82fbac054 · outbound

This paper cites Text2Street: Controllable Text-to-image Generation for Street Views.

MObI: Multimodal Object Inpainting Using Diffusion Models Text2Street: Controllable Text-to-image Generation for Street Views

Reference 50

Resolution: unresolved; no resolver link, observed 2026-08-10T21:56:17.602604Z

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Observation b7f0b73f-2569-4807-a59f-ad57ab385ce9 · outbound

This paper cites Neurad: Neural rendering for autonomous driving.

MObI: Multimodal Object Inpainting Using Diffusion Models Neurad: Neural rendering for autonomous driving

Reference 51

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:56:18.454725Z

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Observation 599c6803-bec8-40f5-b11f-b33c0c77a246 · outbound

This paper cites Pointaugmenting: Cross-modal augmentation for 3d object 10 detection.

MObI: Multimodal Object Inpainting Using Diffusion Models Pointaugmenting: Cross-modal augmentation for 3d object 10 detection

Reference 52

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:56:18.439052Z

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Observation 115f6f95-5471-4827-bfa8-a5ddae4f70af · outbound

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

MObI: Multimodal Object Inpainting Using Diffusion Models CADSim: Robust and Scalable in-the-wild 3D Reconstruction for Controllable Sensor Simulation

Reference 53

Resolution: unresolved; no resolver link, observed 2026-08-10T21:56:17.618547Z

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Observation 0c073766-6195-4621-9bdf-8778ccfbd337 · outbound

This paper cites Diffusion models are geometry critics: Single image 3d editing using pre-trained diffusion priors.

MObI: Multimodal Object Inpainting Using Diffusion Models Diffusion models are geometry critics: Single image 3d editing using pre-trained diffusion priors

Reference 54

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:56:18.423916Z

Source-reported events for the cited work

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Observation 999e3ac6-500f-405f-9d76-745c245996f3 · outbound

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MObI: Multimodal Object Inpainting Using Diffusion Models Unresolved cited work

Reference 55

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This paper cites Editable scene simulation for autonomous driving via collaborative llm-agents.

MObI: Multimodal Object Inpainting Using Diffusion Models Editable scene simulation for autonomous driving via collaborative llm-agents

Reference 56

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This paper cites Panacea: Panoramic and Controllable Video Generation for Autonomous Driving.

MObI: Multimodal Object Inpainting Using Diffusion Models Panacea: Panoramic and Controllable Video Generation for Autonomous Driving

Reference 57

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This paper cites Objectdrop: Bootstrap- ping counterfactuals for photorealistic object removal and in- sertion, 2024.

MObI: Multimodal Object Inpainting Using Diffusion Models Objectdrop: Bootstrap- ping counterfactuals for photorealistic object removal and in- sertion, 2024

Reference 58

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:56:18.376127Z

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Observation be6f34f1-6593-483f-ab7a-ef1d941dd7d6 · outbound

This paper cites Drivescape: To- wards high-resolution controllable multi-view driving video generation, 2024.

MObI: Multimodal Object Inpainting Using Diffusion Models Drivescape: To- wards high-resolution controllable multi-view driving video generation, 2024

Reference 59

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:56:18.358909Z

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Observation 49e66a03-0e25-4810-a4aa-ed2458aeffa1 · outbound

This paper cites Neural Assets: 3D-Aware Multi-Object Scene Synthesis with Image Diffusion Models.

MObI: Multimodal Object Inpainting Using Diffusion Models Neural Assets: 3D-Aware Multi-Object Scene Synthesis with Image Diffusion Models

Reference 60

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Observation 03fbc3cc-656a-4eb3-8746-be76fdde7f8c · outbound

This paper cites Synthetic lidar point cloud generation using deep gen- erative models for improved driving scene object recogni- tion.

MObI: Multimodal Object Inpainting Using Diffusion Models Synthetic lidar point cloud generation using deep gen- erative models for improved driving scene object recogni- tion

Reference 61

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:56:18.341392Z

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Observation c5a06afd-1698-42a5-8614-2d27e2250f53 · outbound

This paper cites X-Drive: Cross-modality consistent multi-sensor data synthesis for driving scenarios.

MObI: Multimodal Object Inpainting Using Diffusion Models X-Drive: Cross-modality consistent multi-sensor data synthesis for driving scenarios

Reference 62

Resolution: unresolved; no resolver link, observed 2026-08-10T21:56:17.665000Z

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Observation 288e9a4c-977f-4364-ba3f-b1a77c14b761 · outbound

This paper cites Ultralidar: Learning compact representations for lidar completion and generation, 2023.

MObI: Multimodal Object Inpainting Using Diffusion Models Ultralidar: Learning compact representations for lidar completion and generation, 2023

Reference 63

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:56:18.325513Z

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Observation b831dfac-4cf9-4b0a-85b1-23889abe4ff3 · outbound

This paper cites Second: Sparsely embed- ded convolutional detection.

MObI: Multimodal Object Inpainting Using Diffusion Models Second: Sparsely embed- ded convolutional detection

Reference 64

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:56:18.309824Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 213ebdca-53de-46ac-8a36-3dc3c9b00eb3 · outbound

This paper cites Paint by example: Exemplar-based image editing with diffusion mod- els.

MObI: Multimodal Object Inpainting Using Diffusion Models Paint by example: Exemplar-based image editing with diffusion mod- els

Reference 65

Resolution: unresolved; no resolver link, observed 2026-08-10T21:56:17.680003Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4859d704-e15c-442a-9548-35b8abd91afb · outbound

This paper cites BEVControl: Accurately Controlling Street-view Elements with Multi-perspective Consistency via BEV Sketch Layout.

MObI: Multimodal Object Inpainting Using Diffusion Models BEVControl: Accurately Controlling Street-view Elements with Multi-perspective Consistency via BEV Sketch Layout

Reference 66

Resolution: unresolved; no resolver link, observed 2026-08-10T21:56:17.685225Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 50ea3ab9-1c21-4998-80da-c29459aa7a8e · outbound

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

MObI: Multimodal Object Inpainting Using Diffusion Models Unisim: A neural closed-loop sensor simulator

Reference 67

Resolution: unresolved; no resolver link, observed 2026-08-10T21:56:17.690608Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8a159840-ff0e-4713-a2d8-732730d85113 · outbound

This paper cites Image sculpting: Precise ob- ject editing with 3d geometry control.

MObI: Multimodal Object Inpainting Using Diffusion Models Image sculpting: Precise ob- ject editing with 3d geometry control

Reference 68

Resolution: unresolved; no resolver link, observed 2026-08-10T21:56:17.695789Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 71297ca1-1fc4-4c5e-aa62-82bc5664404c · outbound

This paper cites CustomNet: Zero-shot Object Customization with Variable-Viewpoints in Text-to-Image Diffusion Models.

MObI: Multimodal Object Inpainting Using Diffusion Models CustomNet: Zero-shot Object Customization with Variable-Viewpoints in Text-to-Image Diffusion Models

Reference 69

Resolution: unresolved; no resolver link, observed 2026-08-10T21:56:17.700708Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation dd182fbb-1323-4358-8e89-a5c0f121f271 · outbound

This paper cites Cutmix: Regu- larization strategy to train strong classifiers with localizable features.

MObI: Multimodal Object Inpainting Using Diffusion Models Cutmix: Regu- larization strategy to train strong classifiers with localizable features

Reference 70

Resolution: unresolved; no resolver link, observed 2026-08-10T21:56:17.705609Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d401580e-7a4f-49cf-8029-b6641e72d82a · outbound

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

MObI: Multimodal Object Inpainting Using Diffusion Models Adding conditional control to text-to-image diffusion models

Reference 71

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:56:18.252192Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 5948a2db-566b-478e-9d15-69a47fb94106 · outbound

This paper cites The unreasonable effectiveness of deep features as a perceptual metric.

MObI: Multimodal Object Inpainting Using Diffusion Models The unreasonable effectiveness of deep features as a perceptual metric

Reference 72

Resolution: unresolved; no resolver link, observed 2026-08-10T21:56:17.714885Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 87f578b1-96b1-48c8-a829-cbbe8dd1c479 · outbound

This paper cites Exploring Data Augmentation for Multi-Modality 3D Object Detection.

MObI: Multimodal Object Inpainting Using Diffusion Models Exploring Data Augmentation for Multi-Modality 3D Object Detection

Reference 73

Resolution: unresolved; no resolver link, observed 2026-08-10T21:56:17.719381Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 91af7488-f78d-4083-b10b-2e4b0d54dfd9 · outbound

This paper cites Scene-Conditional 3D Object Stylization and Composition.

MObI: Multimodal Object Inpainting Using Diffusion Models Scene-Conditional 3D Object Stylization and Composition

Reference 74

Resolution: unresolved; no resolver link, observed 2026-08-10T21:56:17.724151Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 773076ce-60f6-4c5b-b9f5-e615be42e263 · outbound

This paper cites Learning to generate realistic lidar point clouds, 2022.

MObI: Multimodal Object Inpainting Using Diffusion Models Learning to generate realistic lidar point clouds, 2022

Reference 75

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

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