Text-guided Synthetic Geometric Augmentation for Zero-shot 3D Understanding | Paper Citation Record

Observation 537d6944-d501-4450-a1eb-2739c0c4f21a · outbound

This paper cites Visual objects in context.

Text-guided Synthetic Geometric Augmentation for Zero-shot 3D Understanding Visual objects in context

Reference 1

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Observation 1b3e2a0a-9521-4eb8-95d9-84cfde2ddfd6 · outbound

This paper cites The ball-pivoting algo- rithm for surface reconstruction.

Text-guided Synthetic Geometric Augmentation for Zero-shot 3D Understanding The ball-pivoting algo- rithm for surface reconstruction

Reference 2

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Observation 1ce9e8d4-aee0-49ba-bc2e-9d49d7f049e1 · outbound

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

Text-guided Synthetic Geometric Augmentation for Zero-shot 3D Understanding ShapeNet: An Information-Rich 3D Model Repository

Reference 3

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This paper cites Fan- tasia3d: Disentangling geometry and appearance for high- quality text-to-3d content creation.

Text-guided Synthetic Geometric Augmentation for Zero-shot 3D Understanding Fan- tasia3d: Disentangling geometry and appearance for high- quality text-to-3d content creation

Reference 4

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Observation 417b4a71-d6b4-4bd4-a502-941f243f2f47 · outbound

This paper cites Reproducible scal- ing laws for contrastive language-image learning.

Text-guided Synthetic Geometric Augmentation for Zero-shot 3D Understanding Reproducible scal- ing laws for contrastive language-image learning

Reference 5

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Observation 83c0a758-fb15-4b55-80aa-e3b0f6c9d48d · outbound

This paper cites Abo: Dataset and benchmarks for real-world 3d object un- derstanding.

Text-guided Synthetic Geometric Augmentation for Zero-shot 3D Understanding Abo: Dataset and benchmarks for real-world 3d object un- derstanding

Reference 6

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Observation 9be2118e-f370-4bfd-b777-f8cee3720342 · outbound

This paper cites Objaverse: A universe of annotated 3d objects.

Text-guided Synthetic Geometric Augmentation for Zero-shot 3D Understanding Objaverse: A universe of annotated 3d objects

Reference 7

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This paper cites Objaverse-xl: A universe of 10m+ 3d objects.

Text-guided Synthetic Geometric Augmentation for Zero-shot 3D Understanding Objaverse-xl: A universe of 10m+ 3d objects

Reference 8

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Observation 024217e1-73ad-403c-a9d2-40e780953a50 · outbound

This paper cites 3d-future: 3d fur- niture shape with texture.

Text-guided Synthetic Geometric Augmentation for Zero-shot 3D Understanding 3d-future: 3d fur- niture shape with texture

Reference 9

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Observation bd1e5d8a-bea1-4533-93c7-40191fd1bde9 · outbound

This paper cites Sculpting holistic 3d representation in con- trastive language-image-3d pre-training.

Text-guided Synthetic Geometric Augmentation for Zero-shot 3D Understanding Sculpting holistic 3d representation in con- trastive language-image-3d pre-training

Reference 10

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This paper cites Generative adversarial networks.

Text-guided Synthetic Geometric Augmentation for Zero-shot 3D Understanding Generative adversarial networks

Reference 11

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Observation 3781a14f-cacc-424c-9238-ab080d456126 · outbound

This paper cites T$^3$Bench: Benchmarking Current Progress in Text-to-3D Generation.

Text-guided Synthetic Geometric Augmentation for Zero-shot 3D Understanding T$^3$Bench: Benchmarking Current Progress in Text-to-3D Generation

Reference 12

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Observation 3dccb1d1-e017-4e7f-b016-920e59999bba · outbound

This paper cites Clip goes 3d: Leveraging prompt tuning for language grounded 3d recognition.

Text-guided Synthetic Geometric Augmentation for Zero-shot 3D Understanding Clip goes 3d: Leveraging prompt tuning for language grounded 3d recognition

Reference 13

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Observation b172c70d-2ab3-472e-a712-fc800d784639 · outbound

This paper cites Clip2point: Transfer clip to point cloud classifi- cation with image-depth pre-training.

Text-guided Synthetic Geometric Augmentation for Zero-shot 3D Understanding Clip2point: Transfer clip to point cloud classifi- cation with image-depth pre-training

Reference 14

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Observation 7ad11958-fdef-45fa-b268-3df8bf5526f4 · outbound

This paper cites When faking your data actually helps – learn- ing vision from GANs, NeRFs, and noise, 2022.

Text-guided Synthetic Geometric Augmentation for Zero-shot 3D Understanding When faking your data actually helps – learn- ing vision from GANs, NeRFs, and noise, 2022

Reference 15

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Observation c0b63a09-9c7d-44ef-98bb-a964c11ca13b · outbound

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

Text-guided Synthetic Geometric Augmentation for Zero-shot 3D Understanding Shap-E: Generating Conditional 3D Implicit Functions

Reference 16

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Observation 38939eab-ed09-425e-baee-9447f38d335c · outbound

This paper cites Object category structure in response patterns of neuronal population in monkey inferior temporal cortex.

Text-guided Synthetic Geometric Augmentation for Zero-shot 3D Understanding Object category structure in response patterns of neuronal population in monkey inferior temporal cortex

Reference 17

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Observation 0ac807a0-2416-4b9a-b5a6-e5b823702aca · outbound

This paper cites Auto-Encoding Variational Bayes.

Text-guided Synthetic Geometric Augmentation for Zero-shot 3D Understanding Auto-Encoding Variational Bayes

Reference 18

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Observation eb9c210b-bb08-4326-afaa-2fb1435e4496 · outbound

This paper cites Blip-2: Bootstrapping language-image pre-training with frozen image encoders and large language models.

Text-guided Synthetic Geometric Augmentation for Zero-shot 3D Understanding Blip-2: Bootstrapping language-image pre-training with frozen image encoders and large language models

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T20:11:26.480120Z

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Observation 0accee5a-ef00-4421-9fc9-6d88088740c4 · outbound

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

Text-guided Synthetic Geometric Augmentation for Zero-shot 3D Understanding Magic3d: High-resolution text-to-3d content creation

Reference 20

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This paper cites Openshape: Scaling up 3d shape representation towards open-world understanding.

Text-guided Synthetic Geometric Augmentation for Zero-shot 3D Understanding Openshape: Scaling up 3d shape representation towards open-world understanding

Reference 21

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Observation fe8b178d-ed7e-4b50-82ed-278e77096ad3 · outbound

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

Text-guided Synthetic Geometric Augmentation for Zero-shot 3D Understanding Zero-1-to- 3: Zero-shot one image to 3d object

Reference 22

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Observation bf2c973e-44ce-48e5-8f55-bcd169e9afa1 · outbound

This paper cites Decoupled Weight Decay Regularization.

Text-guided Synthetic Geometric Augmentation for Zero-shot 3D Understanding Decoupled Weight Decay Regularization

Reference 23

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Observation ea79f73f-95f0-4bfd-abbc-3944e0946b1a · outbound

This paper cites SGDR: Stochastic Gradient Descent with Warm Restarts.

Text-guided Synthetic Geometric Augmentation for Zero-shot 3D Understanding SGDR: Stochastic Gradient Descent with Warm Restarts

Reference 24

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Observation 7c0ed55d-004e-459f-bdc1-31a92d67398c · outbound

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

Text-guided Synthetic Geometric Augmentation for Zero-shot 3D Understanding GLIDE: Towards Photorealistic Image Generation and Editing with Text-Guided Diffusion Models

Reference 25

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Observation b9ed81d5-24b0-4a76-aaac-7852bbba9c8c · outbound

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

Text-guided Synthetic Geometric Augmentation for Zero-shot 3D Understanding Point-E: A System for Generating 3D Point Clouds from Complex Prompts

Reference 26

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Observation 57ae5f8b-8752-4a3a-bc85-6f63ba1575d9 · outbound

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

Text-guided Synthetic Geometric Augmentation for Zero-shot 3D Understanding DINOv2: Learning Robust Visual Features without Supervision

Reference 27

Resolution: unresolved; no resolver link, observed 2026-08-10T20:11:25.750383Z

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Observation 3adbb8d8-8553-46b8-9cca-a24a37a3630e · outbound

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

Text-guided Synthetic Geometric Augmentation for Zero-shot 3D Understanding DreamFusion: Text-to-3D using 2D Diffusion

Reference 28

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Observation f3ec796d-bdc1-4588-8976-6906205fcc5a · outbound

This paper cites Contrast with reconstruct: Contrastive 3d representation learning guided by generative pretraining.

Text-guided Synthetic Geometric Augmentation for Zero-shot 3D Understanding Contrast with reconstruct: Contrastive 3d representation learning guided by generative pretraining

Reference 29

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Observation 5506cf46-5b09-47bc-becb-10a70e474c4a · outbound

This paper cites Learn- ing transferable visual models from natural language su- pervision.

Text-guided Synthetic Geometric Augmentation for Zero-shot 3D Understanding Learn- ing transferable visual models from natural language su- pervision

Reference 30

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Observation 5f62484b-7e19-4be6-8c56-dc92b8dbcb5a · outbound

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

Text-guided Synthetic Geometric Augmentation for Zero-shot 3D Understanding High-resolution image synthesis with latent diffusion models

Reference 31

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Observation cefd9dca-36f5-4b6c-9d15-1d83e6c9084d · outbound

This paper cites Photorealistic text-to-image diffusion models with deep language understanding.

Text-guided Synthetic Geometric Augmentation for Zero-shot 3D Understanding Photorealistic text-to-image diffusion models with deep language understanding

Reference 32

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This paper cites Fake it till you make it: Learning trans- ferable representations from synthetic imagenet clones.

Text-guided Synthetic Geometric Augmentation for Zero-shot 3D Understanding Fake it till you make it: Learning trans- ferable representations from synthetic imagenet clones

Reference 33

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Observation 73efbeae-0a75-4c32-8ad2-a517670f31cc · outbound

This paper cites Laion-5b: An open large-scale dataset for training next generation image-text models.

Text-guided Synthetic Geometric Augmentation for Zero-shot 3D Understanding Laion-5b: An open large-scale dataset for training next generation image-text models

Reference 34

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Observation 9aac5709-ef20-40ae-a1d9-9c7045c10f83 · outbound

This paper cites Learning vision from mod- els rivals learning vision from data.

Text-guided Synthetic Geometric Augmentation for Zero-shot 3D Understanding Learning vision from mod- els rivals learning vision from data

Reference 35

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Observation 7998dae5-2495-48b5-8feb-9c6cb9ead6d4 · outbound

This paper cites Stablerep: Synthetic images from text-to- image models make strong visual representation learners.

Text-guided Synthetic Geometric Augmentation for Zero-shot 3D Understanding Stablerep: Synthetic images from text-to- image models make strong visual representation learners

Reference 36

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Observation 65c9c5f1-4222-4e96-9e8a-4f943ee583c4 · outbound

This paper cites Textmesh: Gen- eration of realistic 3d meshes from text prompts.

Text-guided Synthetic Geometric Augmentation for Zero-shot 3D Understanding Textmesh: Gen- eration of realistic 3d meshes from text prompts

Reference 37

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Observation 94662e71-3922-4c4d-b9a5-9d0d5bc7968b · outbound

This paper cites Revisiting point cloud classification: A new benchmark dataset and classification model on real-world data.

Text-guided Synthetic Geometric Augmentation for Zero-shot 3D Understanding Revisiting point cloud classification: A new benchmark dataset and classification model on real-world data

Reference 38

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Observation 54def082-1d2a-41a5-9cf2-fe90b1b6e6b1 · outbound

This paper cites Prolificdreamer: High-fidelity and diverse text-to-3d generation with variational score distilla- tion.

Text-guided Synthetic Geometric Augmentation for Zero-shot 3D Understanding Prolificdreamer: High-fidelity and diverse text-to-3d generation with variational score distilla- tion

Reference 39

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This paper cites 3d shapenets: A deep representation for volumetric shapes.

Text-guided Synthetic Geometric Augmentation for Zero-shot 3D Understanding 3d shapenets: A deep representation for volumetric shapes

Reference 40

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Observation 439c594f-9fb2-4066-99d2-f7c127a31713 · outbound

This paper cites Ulip-2: Towards scalable multimodal pre-training for 3d understanding.

Text-guided Synthetic Geometric Augmentation for Zero-shot 3D Understanding Ulip-2: Towards scalable multimodal pre-training for 3d understanding

Reference 41

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Observation d8b59d65-ecc6-4963-89aa-4754ca03a495 · outbound

This paper cites Uni3D: Exploring Unified 3D Representation at Scale.

Text-guided Synthetic Geometric Augmentation for Zero-shot 3D Understanding Uni3D: Exploring Unified 3D Representation at Scale

Reference 42

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Observation 307f3686-9f76-4194-b9a5-f6d1b15acaa3 · outbound

This paper cites prompt: car prediction: A 3D rendering of a car with a pink and white exterior and a pink interior with red streaks Answer: 5 Word matching 5 Total 10 (safe) Table B.

Text-guided Synthetic Geometric Augmentation for Zero-shot 3D Understanding prompt: car prediction: A 3D rendering of a car with a pink and white exterior and a pink interior with red streaks Answer: 5 Word matching 5 Total 10 (safe) Table B

Reference 47

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T20:11:26.163534Z

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Observation 076535b3-c88e-43d2-b2b2-6e6df306b974 · outbound

This paper cites prompt: sofa prediction: A modern, cream-colored sofa GPT-4 Answer 1 Word matching 5 Total 6 (safe) Table C.

Text-guided Synthetic Geometric Augmentation for Zero-shot 3D Understanding prompt: sofa prediction: A modern, cream-colored sofa GPT-4 Answer 1 Word matching 5 Total 6 (safe) Table C

Reference 51

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Observation 6eb05ba9-2a3b-4cb3-82ea-9c9e20306dae · outbound

This paper cites If the prediction contains information that does not appear in the prompt, it should not be considered as bad.

Text-guided Synthetic Geometric Augmentation for Zero-shot 3D Understanding If the prediction contains information that does not appear in the prompt, it should not be considered as bad

Reference 52

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T20:11:26.215770Z

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This paper cites Do not provide a complete answer; give the score in the format: 3.

Text-guided Synthetic Geometric Augmentation for Zero-shot 3D Understanding Do not provide a complete answer; give the score in the format: 3

Reference 53

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T20:11:26.197989Z

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Observation e1bf9033-6d9d-4f4c-8fb9-ba0152f7cb7d · outbound

This paper cites similar in appearance).

Text-guided Synthetic Geometric Augmentation for Zero-shot 3D Understanding similar in appearance)

Reference 54

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T20:11:26.180280Z

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Observation b1d8335d-d34b-49e6-845f-f366f3668fb9 · outbound

This paper cites prompt: birdhouse prediction: A black and white artistic object GPT-4 Answer 2 Word matching 1 Total 3 (ng) Table D.

Text-guided Synthetic Geometric Augmentation for Zero-shot 3D Understanding prompt: birdhouse prediction: A black and white artistic object GPT-4 Answer 2 Word matching 1 Total 3 (ng) Table D

Reference 55

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T20:11:26.129646Z

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Observation f54af483-3d9d-4608-88f9-54ce6e5356c1 · outbound

This paper cites Details of TeGA A.1.

Text-guided Synthetic Geometric Augmentation for Zero-shot 3D Understanding Details of TeGA A.1

Reference 2023

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