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Paper Citation Record · LEDGER

Point Cloud Understanding via Attention-Driven Contrastive Learning

As of 19 August 2026, this Paper Citation Record lists 68 of 68 outbound references and 0 inbound Pith citation observations for arXiv:2411.14744.

A citation records a reference. It does not transfer a finding from one paper to another.

pith.paper-citation-record.v1
2411.14744 v1

Coverage vector

measured 68 of 68 reference resolution

Typed states for the displayed outbound observations.

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measured 68 of 68 standing notices

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measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

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measured 0 of 1 external citation measurements

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Reference resolution

68 of 68 outbound references displayed

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External citation measurements

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Outbound references

Observation baea57f2-e29f-4aac-b4e6-3b9285664b01 · outbound

This paper cites Maskclr: Attention-guided contrastive learning for robust action representation learning.

Point Cloud Understanding via Attention-Driven Contrastive Learning Maskclr: Attention-guided contrastive learning for robust action representation learning

Reference 1

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Observation 93738aad-904d-4f6e-be0e-0f648a6930e0 · outbound

This paper cites Learning representations and generative models for 3d point clouds.

Point Cloud Understanding via Attention-Driven Contrastive Learning Learning representations and generative models for 3d point clouds

Reference 2

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Observation 552df88a-6957-485f-8354-9aaa8c3b12de · outbound

This paper cites An overview of augmented reality.

Point Cloud Understanding via Attention-Driven Contrastive Learning An overview of augmented reality

Reference 3

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Observation 1bca8966-b585-4f3b-92f0-c31166da9713 · outbound

This paper cites BEiT: BERT Pre-Training of Image Transformers.

Point Cloud Understanding via Attention-Driven Contrastive Learning BEiT: BERT Pre-Training of Image Transformers

Reference 4

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Observation 271b9934-8e53-453f-bda2-1809859d7b11 · outbound

This paper cites Pointgpt: Auto-regressively generative pre- training from point clouds.

Point Cloud Understanding via Attention-Driven Contrastive Learning Pointgpt: Auto-regressively generative pre- training from point clouds

Reference 5

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Observation ad33447d-4677-4c73-82c0-376cfbc734b9 · outbound

This paper cites 3d point cloud processing and learning for autonomous driving: Impacting map cre- ation, localization, and perception.

Point Cloud Understanding via Attention-Driven Contrastive Learning 3d point cloud processing and learning for autonomous driving: Impacting map cre- ation, localization, and perception

Reference 6

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Observation 79ad3b31-c76d-40b7-9b0f-585da9480d27 · outbound

This paper cites Multi-view 3d object detection network for autonomous driving.

Point Cloud Understanding via Attention-Driven Contrastive Learning Multi-view 3d object detection network for autonomous driving

Reference 7

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Observation 07db0219-6b67-403b-af58-9ba59cb9a43f · outbound

This paper cites Pra-net: Point relation-aware network for 3d point cloud analysis.

Point Cloud Understanding via Attention-Driven Contrastive Learning Pra-net: Point relation-aware network for 3d point cloud analysis

Reference 8

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Observation 2ff5ff91-4bb5-4ff1-bb2f-1da9636da940 · outbound

This paper cites BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding.

Point Cloud Understanding via Attention-Driven Contrastive Learning BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding

Reference 9

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Observation a5ce1970-c754-45e2-82b0-9f3b6d8701f0 · outbound

This paper cites Autoencoders as Cross-Modal Teachers: Can Pretrained 2D Image Transformers Help 3D Representation Learning?.

Point Cloud Understanding via Attention-Driven Contrastive Learning Autoencoders as Cross-Modal Teachers: Can Pretrained 2D Image Transformers Help 3D Representation Learning?

Reference 10

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Observation 407ab37b-efcc-4850-bb23-f48aa469b912 · outbound

This paper cites Why does unsupervised pre-training help deep learning? In Proceedings of the thirteenth international con- ference on artificial intelligence and statistics , pages 201–.

Point Cloud Understanding via Attention-Driven Contrastive Learning Why does unsupervised pre-training help deep learning? In Proceedings of the thirteenth international con- ference on artificial intelligence and statistics , pages 201–

Reference 11

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Observation be9fb503-9fad-4c05-bdf8-0f6184bd744e · outbound

This paper cites Shape2Scene: 3D Scene Representation Learning Through Pre-training on Shape Data.

Point Cloud Understanding via Attention-Driven Contrastive Learning Shape2Scene: 3D Scene Representation Learning Through Pre-training on Shape Data

Reference 12

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Observation 4d672c25-1a7c-486e-afdd-7fa45cdee83b · outbound

This paper cites Point cloud interaction and ma- nipulation in virtual reality.

Point Cloud Understanding via Attention-Driven Contrastive Learning Point cloud interaction and ma- nipulation in virtual reality

Reference 13

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Observation ed330813-9031-4514-a097-ea5b435e7456 · outbound

This paper cites Generative adversarial networks.

Point Cloud Understanding via Attention-Driven Contrastive Learning Generative adversarial networks

Reference 14

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Observation d14cfb5c-4947-4347-863a-4e09a934de8c · outbound

This paper cites Mvtn: Multi-view transformation network for 3d shape recognition.

Point Cloud Understanding via Attention-Driven Contrastive Learning Mvtn: Multi-view transformation network for 3d shape recognition

Reference 15

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Observation 3b3998e8-d8b4-42c8-a0ed-2a2b280c95ca · outbound

This paper cites Mamba3D: Enhancing Local Features for 3D Point Cloud Analysis via State Space Model.

Point Cloud Understanding via Attention-Driven Contrastive Learning Mamba3D: Enhancing Local Features for 3D Point Cloud Analysis via State Space Model

Reference 16

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Observation c7ed3567-2dd1-4428-a8aa-0b399279857b · outbound

This paper cites Masked autoencoders are scalable vision learners.

Point Cloud Understanding via Attention-Driven Contrastive Learning Masked autoencoders are scalable vision learners

Reference 17

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Observation 409ed794-3888-4d72-9094-b41ad1c0a56a · outbound

This paper cites Atten- tion discriminant sampling for point clouds.

Point Cloud Understanding via Attention-Driven Contrastive Learning Atten- tion discriminant sampling for point clouds

Reference 18

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Observation 52fed73b-6848-4b25-92c8-7d521c8ccee3 · outbound

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

Point Cloud Understanding via Attention-Driven Contrastive Learning Clip2point: Transfer clip to point cloud classifica- tion with image-depth pre-training

Reference 19

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Observation 891c9b6c-7704-4d13-9a83-70f91c754705 · outbound

This paper cites Self-supervised Modal and View Invariant Feature Learning.

Point Cloud Understanding via Attention-Driven Contrastive Learning Self-supervised Modal and View Invariant Feature Learning

Reference 20

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Observation 4e497889-cf0e-45b5-a7d3-eb91c5a07d8c · outbound

This paper cites So-net: Self- organizing network for point cloud analysis.

Point Cloud Understanding via Attention-Driven Contrastive Learning So-net: Self- organizing network for point cloud analysis

Reference 21

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Observation 8995eed4-fc78-4f2e-a036-3db849fa5060 · outbound

This paper cites Pointcnn: Convolution on x-transformed points.

Point Cloud Understanding via Attention-Driven Contrastive Learning Pointcnn: Convolution on x-transformed points

Reference 22

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Observation 4cf7ce91-4992-4b21-b1f0-f49c3cdf5cec · outbound

This paper cites General point model pretrain- ing with autoencoding and autoregressive.

Point Cloud Understanding via Attention-Driven Contrastive Learning General point model pretrain- ing with autoencoding and autoregressive

Reference 23

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Observation 2c10a092-53d5-423a-8b04-1cd07a0c6541 · outbound

This paper cites Pointmamba: A simple state space model for point cloud analysis.

Point Cloud Understanding via Attention-Driven Contrastive Learning Pointmamba: A simple state space model for point cloud analysis

Reference 24

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Observation 724bfbbc-df71-4009-a169-73059417a34c · outbound

This paper cites Masked dis- crimination for self-supervised learning on point clouds.

Point Cloud Understanding via Attention-Driven Contrastive Learning Masked dis- crimination for self-supervised learning on point clouds

Reference 25

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Observation 7e157fe1-aed5-44c4-8750-d2e87c4fb250 · outbound

This paper cites Point Mamba: A Novel Point Cloud Backbone Based on State Space Model with Octree-Based Ordering Strategy.

Point Cloud Understanding via Attention-Driven Contrastive Learning Point Mamba: A Novel Point Cloud Backbone Based on State Space Model with Octree-Based Ordering Strategy

Reference 26

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Observation bd8bbbb6-7c46-432e-8697-0e52742f2bba · outbound

This paper cites Deep image translation with an affinity-based change prior for un- supervised multimodal change detection.

Point Cloud Understanding via Attention-Driven Contrastive Learning Deep image translation with an affinity-based change prior for un- supervised multimodal change detection

Reference 27

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Observation 4a1836a8-9e89-47a7-8090-23b3fe5ba22f · outbound

This paper cites Rethinking Network Design and Local Geometry in Point Cloud: A Simple Residual MLP Framework.

Point Cloud Understanding via Attention-Driven Contrastive Learning Rethinking Network Design and Local Geometry in Point Cloud: A Simple Residual MLP Framework

Reference 28

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Observation 763ddcc8-90f7-434c-8329-72c51434dae1 · outbound

This paper cites Occupancy-MAE: Self-supervised Pre-training Large-scale LiDAR Point Clouds with Masked Occupancy Autoencoders.

Point Cloud Understanding via Attention-Driven Contrastive Learning Occupancy-MAE: Self-supervised Pre-training Large-scale LiDAR Point Clouds with Masked Occupancy Autoencoders

Reference 29

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Observation 3b7e714c-4da6-49af-9a7d-dc0e128b9988 · outbound

This paper cites Self-supervised learning of pretext-invariant representations.

Point Cloud Understanding via Attention-Driven Contrastive Learning Self-supervised learning of pretext-invariant representations

Reference 30

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Observation cd8a7d5d-3144-4e22-8658-40d13b843386 · outbound

This paper cites From image collections to point clouds with self-supervised shape and pose networks.

Point Cloud Understanding via Attention-Driven Contrastive Learning From image collections to point clouds with self-supervised shape and pose networks

Reference 31

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Observation 3b5c2cde-b822-47b0-b29e-6facd05f3efb · outbound

This paper cites Masked autoencoders for point cloud self-supervised learning.

Point Cloud Understanding via Attention-Driven Contrastive Learning Masked autoencoders for point cloud self-supervised learning

Reference 32

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Observation 54a3fb0a-c889-4ced-9def-cc64ad5bfebe · outbound

This paper cites Pointnet: Deep learning on point sets for 3d classification and segmentation.

Point Cloud Understanding via Attention-Driven Contrastive Learning Pointnet: Deep learning on point sets for 3d classification and segmentation

Reference 33

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Observation 5a551712-1e2f-453f-ae56-92f25d82190c · outbound

This paper cites Pointnet++: Deep hierarchical feature learning on point sets in a metric space.

Point Cloud Understanding via Attention-Driven Contrastive Learning Pointnet++: Deep hierarchical feature learning on point sets in a metric space

Reference 34

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Observation 0da31cb1-6f0d-4c1e-b504-9fcf36d92628 · outbound

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

Point Cloud Understanding via Attention-Driven Contrastive Learning Contrast with reconstruct: Contrastive 3d representation learning guided by generative pretraining

Reference 35

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Observation 7b78220e-d998-47e8-ac57-26d484525521 · outbound

This paper cites Shapellm: Universal 3d object understanding for embodied interaction.

Point Cloud Understanding via Attention-Driven Contrastive Learning Shapellm: Universal 3d object understanding for embodied interaction

Reference 36

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-12T15:02:29.444104Z digest=sha256:b3a12647b04df7d7b51e0badfe5d65c9424f06cc518185eff4a05676794c0fd8

Observation 5bc303ed-03af-457c-9633-793c0dba9e61 · outbound

This paper cites Pointnext: Revisiting pointnet++ with improved training and scaling strategies.

Point Cloud Understanding via Attention-Driven Contrastive Learning Pointnext: Revisiting pointnet++ with improved training and scaling strategies

Reference 37

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raw_fallback, observed 2026-08-12T15:02:30.116722Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-12T15:02:29.448658Z digest=sha256:f803e2f321bbec01ce6b04f6827b6d6112b6f7523291a013a6afe67e8b519e9c

Observation 207d52b4-4663-4059-b623-a465854edb5d · outbound

This paper cites Spatiotempo- ral contrastive video representation learning.

Point Cloud Understanding via Attention-Driven Contrastive Learning Spatiotempo- ral contrastive video representation learning

Reference 38

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T15:02:30.102771Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation 345cf29e-b129-4ab6-b0a5-f699a11f5079 · outbound

This paper cites Improving language understanding by gener- ative pre-training.

Point Cloud Understanding via Attention-Driven Contrastive Learning Improving language understanding by gener- ative pre-training

Reference 39

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unresolved
no resolver link, observed 2026-08-12T15:02:29.456807Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T15:02:29.456807Z digest=sha256:205e0cb69a05174027dc7a7a7475350328f762ada25e5d89c17a20d26b6eef7c

Observation 3427be56-0e2b-43cf-8e06-508d9fed31a4 · outbound

This paper cites Surface representa- tion for point clouds.

Point Cloud Understanding via Attention-Driven Contrastive Learning Surface representa- tion for point clouds

Reference 40

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T15:02:30.080296Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-12T15:02:29.460969Z digest=sha256:f82602215abe1dc9c775b75a329fb7f52aaea8bf2647875fa2c7ed81fa8789cd

Observation 95c965bf-06fd-4060-b008-630f6f064a7c · outbound

This paper cites Point-JEPA: A Joint Embedding Predictive Architecture for Self-Supervised Learning on Point Cloud.

Point Cloud Understanding via Attention-Driven Contrastive Learning Point-JEPA: A Joint Embedding Predictive Architecture for Self-Supervised Learning on Point Cloud

Reference 41

Resolution
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no resolver link, observed 2026-08-12T15:02:29.465805Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T15:02:29.465805Z digest=sha256:1df49a23e612713236ae8f5e77c428f83620dbe308cc5f1fde44ae2da2b1f4b9

Observation b80f86a0-76c7-4ee6-9633-87c60bf0ea00 · outbound

This paper cites Detecting formal thought disorder by deep contextualized word representations.

Point Cloud Understanding via Attention-Driven Contrastive Learning Detecting formal thought disorder by deep contextualized word representations

Reference 42

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T15:02:30.065560Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-12T15:02:29.470436Z digest=sha256:ae7db00f8ad7096906f79dc7615a925d003969b4bf33f5582f35cb6ccc721b0f

Observation 196242b6-a3c3-401e-811b-e5b6b5c3f96a · outbound

This paper cites Self-supervised deep learning on point clouds by reconstructing space.

Point Cloud Understanding via Attention-Driven Contrastive Learning Self-supervised deep learning on point clouds by reconstructing space

Reference 43

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T15:02:30.050442Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-12T15:02:29.474611Z digest=sha256:6adec73b82c659f566dd295104af6237a8ec6273e9e73302f263a98a83f45e2f

Observation a27fb856-ee6c-407a-9fa0-14a56b88ff94 · outbound

This paper cites Exploring 3d navigation: combining speed-coupled flying with orbiting.

Point Cloud Understanding via Attention-Driven Contrastive Learning Exploring 3d navigation: combining speed-coupled flying with orbiting

Reference 44

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T15:02:30.035371Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-12T15:02:29.478811Z digest=sha256:75bb865302560294ada434f9b42b15d78281f51e6ea39c1ce96a6a8749fe071d

Observation a4084798-037f-4d0a-a9f4-9d8594038c98 · outbound

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

Point Cloud Understanding via Attention-Driven Contrastive Learning Revisiting point cloud classification: A new benchmark dataset and classification model on real-world data

Reference 45

Resolution
unresolved
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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T15:02:29.482839Z digest=sha256:27c6a53192670585f45c3220750d8d2ccba2cb01c4d0b462a70d40efea8dd7e3

Observation ad7495c6-c6ef-43b2-b531-4a03efec5a8c · outbound

This paper cites Unsupervised point cloud pre-training via oc- clusion completion.

Point Cloud Understanding via Attention-Driven Contrastive Learning Unsupervised point cloud pre-training via oc- clusion completion

Reference 46

Resolution
unresolved
no resolver link, observed 2026-08-12T15:02:29.487158Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T15:02:29.487158Z digest=sha256:9a03aa1491cc4d0e6815e479729753cfe287020239d8d6ebacd07b90242eb1da

Observation d2f491c3-6221-45f9-97f9-c21f382edbd9 · outbound

This paper cites Dynamic graph cnn for learning on point clouds.

Point Cloud Understanding via Attention-Driven Contrastive Learning Dynamic graph cnn for learning on point clouds

Reference 47

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T15:02:30.003191Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-12T15:02:29.492160Z digest=sha256:ecbd2792887b23c62dd40f323bf577dc0be5f36f1eef237495f9f949440a689b

Observation 401ba033-b8ec-43ee-ac0f-7720c3f11dd0 · outbound

This paper cites P2p: Tuning pre-trained image models for point cloud analysis with point-to-pixel prompting.

Point Cloud Understanding via Attention-Driven Contrastive Learning P2p: Tuning pre-trained image models for point cloud analysis with point-to-pixel prompting

Reference 48

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T15:02:29.988861Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-12T15:02:29.496362Z digest=sha256:514350a54df5cb986867aa4653b7ce19f7c286864b223b41923998d435ae7810

Observation 6706fcdb-20f7-4a7f-92e2-b3d6e59969e0 · outbound

This paper cites PoinTramba: A Hybrid Transformer-Mamba Framework for Point Cloud Analysis.

Point Cloud Understanding via Attention-Driven Contrastive Learning PoinTramba: A Hybrid Transformer-Mamba Framework for Point Cloud Analysis

Reference 49

Resolution
unresolved
no resolver link, observed 2026-08-12T15:02:29.500659Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T15:02:29.500659Z digest=sha256:565e91382141072247d45e3d3474b8752846bfacb74bf21833f5c4a86ea08337

Observation 42770447-8211-4bbf-a029-9ee1a73db0da · outbound

This paper cites Point transformer v3: Simpler faster stronger.

Point Cloud Understanding via Attention-Driven Contrastive Learning Point transformer v3: Simpler faster stronger

Reference 50

Resolution
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no resolver link, observed 2026-08-12T15:02:29.505240Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T15:02:29.505240Z digest=sha256:65aba4123857c12e1216574ad9eda0345030f6239c395dd2fb038dab5d0d7deb

Observation e4c35407-5f76-46c1-b3c7-a400b21db2b5 · outbound

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

Point Cloud Understanding via Attention-Driven Contrastive Learning 3d shapenets: A deep representation for volumetric shapes

Reference 51

Resolution
unresolved
no resolver link, observed 2026-08-12T15:02:29.509545Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T15:02:29.509545Z digest=sha256:66bcb73a5a96044213aa7175f298d574f1a8fe5b889a12eb41af7c06618ca76d

Observation 9e7ead83-494e-4f1d-9e7e-93ea2c9a34bd · outbound

This paper cites Pointcontrast: Unsupervised pre- training for 3d point cloud understanding.

Point Cloud Understanding via Attention-Driven Contrastive Learning Pointcontrast: Unsupervised pre- training for 3d point cloud understanding

Reference 52

Resolution
unresolved
no resolver link, observed 2026-08-12T15:02:29.513864Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T15:02:29.513864Z digest=sha256:6f084ce6b3a9c6efc36402fec6a3b0f50aa956a41f30571a142b74e5e5ac4330

Observation c7b9612c-8a16-4c73-b3de-a19dfcdf13e4 · outbound

This paper cites Ulip: Learning a unified representation of language, images, and point clouds for 3d understanding.

Point Cloud Understanding via Attention-Driven Contrastive Learning Ulip: Learning a unified representation of language, images, and point clouds for 3d understanding

Reference 53

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T15:02:29.947952Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-12T15:02:29.517961Z digest=sha256:2ee3a39ae703696e4b1ba45e790186a186114861d81057e0e378146ff135bc3c

Observation 3fd99a41-bfc4-4a1d-b347-ab2b206466f0 · outbound

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

Point Cloud Understanding via Attention-Driven Contrastive Learning Ulip-2: Towards scalable multimodal pre-training for 3d understanding

Reference 54

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T15:02:29.933619Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-12T15:02:29.522683Z digest=sha256:ad66ba9c31e63fa9af0372621ae01b7c003a6fbf61b18823ac69996030268a43

Observation 0022ba92-18df-41de-b3b3-f098cbc82e62 · outbound

This paper cites A scalable active framework for region annotation in 3d shape collections.ACM Transactions on Graphics (ToG), 35(6):1–12, 2016.

Point Cloud Understanding via Attention-Driven Contrastive Learning A scalable active framework for region annotation in 3d shape collections.ACM Transactions on Graphics (ToG), 35(6):1–12, 2016

Reference 55

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T15:02:29.917595Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-12T15:02:29.526959Z digest=sha256:5ef3cffc18518c6be57b2e39076c9efd43db39f9f04037c949191cf0c397e4c6

Observation b93b111f-4656-41af-8374-a32db048e2b7 · outbound

This paper cites Seq- gan: Sequence generative adversarial nets with policy gra- dient.

Point Cloud Understanding via Attention-Driven Contrastive Learning Seq- gan: Sequence generative adversarial nets with policy gra- dient

Reference 56

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T15:02:29.903174Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-12T15:02:29.531601Z digest=sha256:96651e95b33f1d9ac4f8ac3693ccd0d593f2d2c34166672d3f59f767f15bbb25

Observation 3710a2b5-8b8f-4b9f-916e-3931aedfa8d1 · outbound

This paper cites Point-bert: Pre-training 3d point cloud transformers with masked point modeling.

Point Cloud Understanding via Attention-Driven Contrastive Learning Point-bert: Pre-training 3d point cloud transformers with masked point modeling

Reference 57

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T15:02:29.889051Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-12T15:02:29.536245Z digest=sha256:553b166ab34ed1680d23b5f6e616748898f1d56c1c9535a4adf8678c09bcb6a1

Observation b701f068-8c08-45b3-b379-d6363e0a1d7d · outbound

This paper cites Towards compact 3d representations via point feature enhancement masked au- toencoders.

Point Cloud Understanding via Attention-Driven Contrastive Learning Towards compact 3d representations via point feature enhancement masked au- toencoders

Reference 58

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T15:02:29.873905Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-12T15:02:29.540700Z digest=sha256:90b7a00ce5be77ca8f425b5904453ec0d475edc51063c01663e88bc457797a16

Observation 7bbaae1d-fecf-420e-9126-b9799228bff6 · outbound

This paper cites Point-m2ae: multi-scale masked autoencoders for hierarchical point cloud pre-training.

Point Cloud Understanding via Attention-Driven Contrastive Learning Point-m2ae: multi-scale masked autoencoders for hierarchical point cloud pre-training

Reference 59

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T15:02:29.859899Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-12T15:02:29.544977Z digest=sha256:b3350c663417ff84a60fd2d5699fec4aa31e27d353f8d04c643e2d43e1705c50

Observation 344503da-2ed2-40c9-9c09-a612e68aeadf · outbound

This paper cites Pointclip: Point cloud understanding by clip.

Point Cloud Understanding via Attention-Driven Contrastive Learning Pointclip: Point cloud understanding by clip

Reference 60

Resolution
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no resolver link, observed 2026-08-12T15:02:29.549419Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T15:02:29.549419Z digest=sha256:87c6b405cbbd4a41039c3ce2c1f47cbb0e7af1fd736c4801891dc0485d407e1e

Observation cf69d5f5-97ae-4548-9df2-53087ab91c15 · outbound

This paper cites Learning 3d representations from 2d pre-trained models via image-to-point masked autoencoders.

Point Cloud Understanding via Attention-Driven Contrastive Learning Learning 3d representations from 2d pre-trained models via image-to-point masked autoencoders

Reference 61

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no resolver link, observed 2026-08-12T15:02:29.553565Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T15:02:29.553565Z digest=sha256:2eb615d80a89d50c65ee3691241f44b26e0a463de6bc3335dc26d949e0da98a2

Observation d030eed5-aba7-4df7-bc4a-91989fe13600 · outbound

This paper cites Point Cloud Mamba: Point Cloud Learning via State Space Model.

Point Cloud Understanding via Attention-Driven Contrastive Learning Point Cloud Mamba: Point Cloud Learning via State Space Model

Reference 62

Resolution
unresolved
no resolver link, observed 2026-08-12T15:02:29.557826Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T15:02:29.557826Z digest=sha256:0a238d521319a1f42b01c3e3de56dd76004f9a1ffc4cdb2f59c1d0e78b425d51

Observation 39e658a0-db9f-410e-96b5-26df7c8b466d · outbound

This paper cites Self-supervised pretraining of 3d features on any point-cloud.

Point Cloud Understanding via Attention-Driven Contrastive Learning Self-supervised pretraining of 3d features on any point-cloud

Reference 63

Resolution
unresolved
no resolver link, observed 2026-08-12T15:02:29.562532Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T15:02:29.562532Z digest=sha256:2ffcfaff25f30dd694e69c54ad042bb4b9b4e59161d4a4b54243e44ac48dd0e3

Observation 93ba131c-0ebc-4b75-accd-918b46c010f8 · outbound

This paper cites Point cloud pre-training with diffusion models.

Point Cloud Understanding via Attention-Driven Contrastive Learning Point cloud pre-training with diffusion models

Reference 64

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T15:02:29.820880Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-12T15:02:29.567133Z digest=sha256:0e765a57fe4e60e1f85c6c3c16bcdf115427ee98e418baed3984090529d591ef

Observation 6018777d-c94a-4fa7-868d-4559ac5d2b54 · outbound

This paper cites Point- clip v2: Prompting clip and gpt for powerful 3d open-world learning.

Point Cloud Understanding via Attention-Driven Contrastive Learning Point- clip v2: Prompting clip and gpt for powerful 3d open-world learning

Reference 65

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T15:02:29.806971Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-12T15:02:29.571388Z digest=sha256:4ab7fc9d8645fc8869bc38e52ab59e8c08ef56853576a7023ed09de879ecd5e2

Observation aead56e4-fb34-43b6-8ed9-0e4b5d5e8b6f · outbound

This paper cites 3d-vista: Pre-trained transformer for 3d vision and text alignment.

Point Cloud Understanding via Attention-Driven Contrastive Learning 3d-vista: Pre-trained transformer for 3d vision and text alignment

Reference 66

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T15:02:29.793451Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-12T15:02:29.576146Z digest=sha256:dcf3bef53cb9cd0ee8301b5f8c9c395dc7376516292e14f3ccf544cd211aabc1

Observation 3923ae20-b792-4512-a0cd-c139c170e596 · outbound

This paper cites Preliminary Transformer-based self-supervised learning.

Point Cloud Understanding via Attention-Driven Contrastive Learning Preliminary Transformer-based self-supervised learning

Reference 68

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T15:02:29.779374Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-12T15:02:29.580306Z digest=sha256:f645dd8bd359c50ae9fa887155c73e2ed16c7ee8276fad3f68318549042bfe26

Observation 4e389784-8766-4040-a5ca-3b53a61f852d · outbound

This paper cites an unresolved cited work.

Point Cloud Understanding via Attention-Driven Contrastive Learning Unresolved cited work

Reference 208

Resolution
unresolved
raw_fallback, observed 2026-08-12T15:02:30.380498Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-12T15:02:29.336161Z digest=sha256:46dcc53e51d486427685f39b203b8bd39d98bb2d762e0ff8b3454c2b59f85c08

Pith citing papers

No inbound Pith citation observations are available.