Paper Citation Record · LEDGER

Learning from 2D: Contrastive Pixel-to-Point Knowledge Transfer for 3D Pretraining

As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 10 inbound Pith citation observations for arXiv:2104.04687.

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

pith.paper-citation-record.v1
2104.04687 v3

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 10 of 10 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-08T06:32:00.761636+00:00

measured 10 of 10 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-06T21:52:45.058273Z

measured 0 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: arxiv_reference, observed 2026-07-04T03:29:29.479882Z

Reference resolution

0 of 0 outbound references displayed

verified exact0
verified fuzzy0
unresolved0
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation e44a0215-7d7c-44d4-8666-27562dc9f5cb · inbound

High-quality Pseudo-labeling for Point Cloud Segmentation with Scene-level Annotation cites this paper.

High-quality Pseudo-labeling for Point Cloud Segmentation with Scene-level Annotation Learning from 2D: Contrastive Pixel-to-Point Knowledge Transfer for 3D Pretraining

Reference 34

Resolution: unresolved; no resolver link, observed 2026-08-06T21:52:45.058273Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e9a4a2e1-f3b3-4a9c-b717-89febea07e53 · inbound

Beyond One Shot, Beyond One Perspective: Cross-View and Long-Horizon Distillation for Better LiDAR Representations cites this paper.

Beyond One Shot, Beyond One Perspective: Cross-View and Long-Horizon Distillation for Better LiDAR Representations Learning from 2D: Contrastive Pixel-to-Point Knowledge Transfer for 3D Pretraining

Reference 52

Resolution: unresolved; no resolver link, observed 2026-08-06T19:32:34.713298Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d0d9424f-6cf3-4b85-8d1b-bf5e39bf080f · inbound

Multi-modal Multi-task Pre-training for Improved Point Cloud Understanding cites this paper.

Multi-modal Multi-task Pre-training for Improved Point Cloud Understanding Learning from 2D: Contrastive Pixel-to-Point Knowledge Transfer for 3D Pretraining

Reference 2021

Resolution: unresolved; no resolver link, observed 2026-08-06T14:51:52.741538Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9197fa95-24d5-4be9-b2d0-61a2082c7e31 · inbound

Domain Adaptation-Based Crossmodal Knowledge Distillation for 3D Semantic Segmentation cites this paper.

Domain Adaptation-Based Crossmodal Knowledge Distillation for 3D Semantic Segmentation Learning from 2D: Contrastive Pixel-to-Point Knowledge Transfer for 3D Pretraining

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-05T13:43:55.822844Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 509cef8b-b9f1-4191-a4e5-05b43eeb3bf1 · inbound

Bridging the Dimensionality Gap: A Taxonomy and Survey of 2D Vision Model Adaptation for 3D Analysis cites this paper.

Bridging the Dimensionality Gap: A Taxonomy and Survey of 2D Vision Model Adaptation for 3D Analysis Learning from 2D: Contrastive Pixel-to-Point Knowledge Transfer for 3D Pretraining

Reference 4

Resolution: verified exact; arxiv_id, observed 2026-05-13T20:28:13.972698Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation b286709b-4a6c-431c-a246-6fb5d5089503 · inbound

Feasibility of Indoor Frame-Wise Lidar Semantic Segmentation via Distillation from Visual Foundation Model cites this paper.

Feasibility of Indoor Frame-Wise Lidar Semantic Segmentation via Distillation from Visual Foundation Model Learning from 2D: Contrastive Pixel-to-Point Knowledge Transfer for 3D Pretraining

Reference 11

Resolution: metadata mismatch; arxiv_id, observed 2026-05-10T11:35:19.215295Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 5b6f5e5d-827d-4a33-9e2a-e4c39cb80b75 · inbound

Hyperbolic Distillation: Geometry-Guided Cross-Modal Transfer for Robust 3D Object Detection cites this paper.

Hyperbolic Distillation: Geometry-Guided Cross-Modal Transfer for Robust 3D Object Detection Learning from 2D: Contrastive Pixel-to-Point Knowledge Transfer for 3D Pretraining

Reference 27

Resolution: metadata mismatch; arxiv_id, observed 2026-05-12T06:16:28.786473Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 8d79a1f6-4402-4bd1-91d5-1d3947880498 · inbound

HilDA: Hierarchical Distillation with Diffusion for Advancing Self-Supervised LiDAR Pre-training cites this paper.

HilDA: Hierarchical Distillation with Diffusion for Advancing Self-Supervised LiDAR Pre-training Learning from 2D: Contrastive Pixel-to-Point Knowledge Transfer for 3D Pretraining

Reference 50

Resolution: metadata mismatch; arxiv_id, observed 2026-07-04T03:29:29.483040Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 273b026d-264f-48eb-8f70-65743e3559bb · inbound

Cross4D-JEPA: Dense Cross-modal Correspondence Distillation for 4D Point Cloud Representation Learning cites this paper.

Cross4D-JEPA: Dense Cross-modal Correspondence Distillation for 4D Point Cloud Representation Learning Learning from 2D: Contrastive Pixel-to-Point Knowledge Transfer for 3D Pretraining

Reference 19

Resolution: verified exact; arxiv_id, observed 2026-07-02T14:47:03.108630Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 933573ac-84db-456b-beb3-d17fb5880473 · inbound

TOLiD: Bridging the Architecture Gap in Vision Foundation Model to LiDAR Pretraining via Token Lifting for Distillation cites this paper.

TOLiD: Bridging the Architecture Gap in Vision Foundation Model to LiDAR Pretraining via Token Lifting for Distillation Learning from 2D: Contrastive Pixel-to-Point Knowledge Transfer for 3D Pretraining

Reference 10

Resolution: unresolved; no resolver link, observed 2026-07-14T09:28:01.256510Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.