CutS3D: Cutting Semantics in 3D for 2D Unsupervised Instance Segmentation | Paper Citation Record

Observation 3ccbe9bd-9bcc-4fc3-96b5-0c0d0e52a264 · outbound

This paper cites Cuvler: Enhanced unsupervised object discoveries through exhaustive self-supervised transformers.

CutS3D: Cutting Semantics in 3D for 2D Unsupervised Instance Segmentation Cuvler: Enhanced unsupervised object discoveries through exhaustive self-supervised transformers

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T13:19:00.504814Z

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Observation 96e32d9f-6a4e-471b-8bc7-d3fdbeba9518 · outbound

This paper cites ZoeDepth: Zero-shot Transfer by Combining Relative and Metric Depth.

CutS3D: Cutting Semantics in 3D for 2D Unsupervised Instance Segmentation ZoeDepth: Zero-shot Transfer by Combining Relative and Metric Depth

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-12T13:18:59.295990Z

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Observation a23876fb-91d6-4706-ae2e-7b52b6a4f698 · outbound

This paper cites Depth Pro: Sharp Monocular Metric Depth in Less Than a Second.

CutS3D: Cutting Semantics in 3D for 2D Unsupervised Instance Segmentation Depth Pro: Sharp Monocular Metric Depth in Less Than a Second

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-12T13:18:59.301977Z

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Observation fe7868bd-88c0-4e98-b8d3-f6c097388b30 · outbound

This paper cites Cascade r-cnn: High quality object detection and instance segmentation.

CutS3D: Cutting Semantics in 3D for 2D Unsupervised Instance Segmentation Cascade r-cnn: High quality object detection and instance segmentation

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T13:19:00.489041Z

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Observation 0722ac25-fc09-4b92-978b-87cac863d6c7 · outbound

This paper cites Unsupervised learning of visual features by contrasting cluster assignments.

CutS3D: Cutting Semantics in 3D for 2D Unsupervised Instance Segmentation Unsupervised learning of visual features by contrasting cluster assignments

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-12T13:18:59.313562Z

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Observation 559709d6-ff94-4995-a71d-4d2e0ad6b9a5 · outbound

This paper cites Emerg- ing properties in self-supervised vision transformers.

CutS3D: Cutting Semantics in 3D for 2D Unsupervised Instance Segmentation Emerg- ing properties in self-supervised vision transformers

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T13:19:00.461183Z

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Observation d19616cc-bbc4-44df-8aa7-87562e948b9c · outbound

This paper cites Groco: Ground constraint for metric self-supervised monocular depth.

CutS3D: Cutting Semantics in 3D for 2D Unsupervised Instance Segmentation Groco: Ground constraint for metric self-supervised monocular depth

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T13:19:00.444796Z

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Observation 9592c51a-5661-4282-8f7f-ccbe8ed3d53f · outbound

This paper cites Hybrid task cascade for instance seg- mentation.

CutS3D: Cutting Semantics in 3D for 2D Unsupervised Instance Segmentation Hybrid task cascade for instance seg- mentation

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-12T13:18:59.331626Z

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Observation 741b7a60-0ccb-4414-b27d-99d3e3212059 · outbound

This paper cites Masked-attention mask transformer for universal image segmentation.

CutS3D: Cutting Semantics in 3D for 2D Unsupervised Instance Segmentation Masked-attention mask transformer for universal image segmentation

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-12T13:18:59.336611Z

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Observation 625a0b49-c7d2-4f5f-83b6-72bdb044ce63 · outbound

This paper cites Algorithm for solution of a problem of max- imum flow in networks with power estimation.

CutS3D: Cutting Semantics in 3D for 2D Unsupervised Instance Segmentation Algorithm for solution of a problem of max- imum flow in networks with power estimation

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T13:19:00.403862Z

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Observation 53982660-5ca7-46e7-98fa-4aa900e42653 · outbound

This paper cites An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale.

CutS3D: Cutting Semantics in 3D for 2D Unsupervised Instance Segmentation An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-12T13:18:59.346460Z

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Observation 462e63d6-7f30-4d26-a3fc-f67a3601c5fc · outbound

This paper cites The pascal visual object classes (voc) challenge.

CutS3D: Cutting Semantics in 3D for 2D Unsupervised Instance Segmentation The pascal visual object classes (voc) challenge

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-12T13:18:59.351184Z

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Observation 869f4abf-5940-4298-b2af-c2dfbcbb4f38 · outbound

This paper cites Vision meets robotics: The kitti dataset.

CutS3D: Cutting Semantics in 3D for 2D Unsupervised Instance Segmentation Vision meets robotics: The kitti dataset

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-12T13:18:59.355792Z

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Observation 09a257e1-77b6-4eca-8ced-1f1f728fd42d · outbound

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

CutS3D: Cutting Semantics in 3D for 2D Unsupervised Instance Segmentation Sim- ple copy-paste is a strong data augmentation method for in- stance segmentation

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T13:19:00.364626Z

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Observation bfe3ba8c-5b60-439b-a080-492fb6b27c46 · outbound

This paper cites Min-cut based segmentation of point clouds.

CutS3D: Cutting Semantics in 3D for 2D Unsupervised Instance Segmentation Min-cut based segmentation of point clouds

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T13:19:00.347751Z

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Observation aef4c07d-8427-493e-af90-fe1855a4e365 · outbound

This paper cites Lvis: A dataset for large vocabulary instance segmentation.

CutS3D: Cutting Semantics in 3D for 2D Unsupervised Instance Segmentation Lvis: A dataset for large vocabulary instance segmentation

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-12T13:18:59.368954Z

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Observation 0dae59dc-e57b-4930-bc9a-4953e9a1f80a · outbound

This paper cites Unsupervised Semantic Segmentation by Distilling Feature Correspondences.

CutS3D: Cutting Semantics in 3D for 2D Unsupervised Instance Segmentation Unsupervised Semantic Segmentation by Distilling Feature Correspondences

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-12T13:18:59.372919Z

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Observation 221dd6ea-73dd-41d7-8f11-64533b5411d6 · outbound

This paper cites Lotus: Diffusion-based Visual Foundation Model for High-quality Dense Prediction.

CutS3D: Cutting Semantics in 3D for 2D Unsupervised Instance Segmentation Lotus: Diffusion-based Visual Foundation Model for High-quality Dense Prediction

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-12T13:18:59.377928Z

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Observation 7beb9bd7-c655-4247-a542-67d8f691f232 · outbound

This paper cites Mask r-cnn.

CutS3D: Cutting Semantics in 3D for 2D Unsupervised Instance Segmentation Mask r-cnn

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-12T13:18:59.382817Z

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Observation c662fb87-fc37-431b-b4a4-1e35993d2060 · outbound

This paper cites Momentum contrast for unsupervised visual rep- resentation learning.

CutS3D: Cutting Semantics in 3D for 2D Unsupervised Instance Segmentation Momentum contrast for unsupervised visual rep- resentation learning

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-12T13:18:59.387738Z

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Observation e6a5b349-639f-4d79-bfc6-0fdfd87c2d7e · outbound

This paper cites Learning to segment every thing.

CutS3D: Cutting Semantics in 3D for 2D Unsupervised Instance Segmentation Learning to segment every thing

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T13:19:00.294674Z

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Observation 5820ba19-99d9-4934-ae52-75fd81f7a74f · outbound

This paper cites Repurpos- ing diffusion-based image generators for monocular depth estimation.

CutS3D: Cutting Semantics in 3D for 2D Unsupervised Instance Segmentation Repurpos- ing diffusion-based image generators for monocular depth estimation

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T13:19:00.276866Z

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Observation 1fa553bf-1bb8-402c-8ba2-0dbd66d2817f · outbound

This paper cites Eagle: Eigen aggregation learning for object-centric unsupervised semantic segmentation.

CutS3D: Cutting Semantics in 3D for 2D Unsupervised Instance Segmentation Eagle: Eigen aggregation learning for object-centric unsupervised semantic segmentation

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T13:19:00.254062Z

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Observation 18b3c32c-3294-4ce2-a036-b72ca194d924 · outbound

This paper cites Segment any- thing.

CutS3D: Cutting Semantics in 3D for 2D Unsupervised Instance Segmentation Segment any- thing

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T13:19:00.234476Z

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No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 22b2dc2f-c4d1-46c0-b8c9-693f8e42656a · outbound

This paper cites Efficient inference in fully connected crfs with gaussian edge potentials.

CutS3D: Cutting Semantics in 3D for 2D Unsupervised Instance Segmentation Efficient inference in fully connected crfs with gaussian edge potentials

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T13:19:00.214438Z

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Observation 1c2f364f-c6f6-4e29-96d4-c888e4f4f8b4 · outbound

This paper cites Promerge: Prompt and merge for unsupervised instance segmentation.

CutS3D: Cutting Semantics in 3D for 2D Unsupervised Instance Segmentation Promerge: Prompt and merge for unsupervised instance segmentation

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T13:19:00.195310Z

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Observation d5cea7b8-0b20-4f73-877c-f9033462c954 · outbound

This paper cites Microsoft coco: Common objects in context.

CutS3D: Cutting Semantics in 3D for 2D Unsupervised Instance Segmentation Microsoft coco: Common objects in context

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T13:19:00.177751Z

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Observation f88d8983-fb34-4de5-b01d-56e560141ea8 · outbound

This paper cites Unsupervised dense predic- tion using differentiable normalized cuts.

CutS3D: Cutting Semantics in 3D for 2D Unsupervised Instance Segmentation Unsupervised dense predic- tion using differentiable normalized cuts

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T13:19:00.159937Z

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No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 167e71cd-192b-470e-a1d8-853c03c02f9c · outbound

This paper cites Image enhancement by unsharp masking the depth buffer.

CutS3D: Cutting Semantics in 3D for 2D Unsupervised Instance Segmentation Image enhancement by unsharp masking the depth buffer

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T13:19:00.136506Z

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Observation acd048e2-3e24-493c-918d-ce4e8da537d2 · outbound

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

CutS3D: Cutting Semantics in 3D for 2D Unsupervised Instance Segmentation DINOv2: Learning Robust Visual Features without Supervision

Reference 30

Resolution: unresolved; no resolver link, observed 2026-08-12T13:18:59.436696Z

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Observation 05e7cb71-4dbf-404b-85a6-af7471c60140 · outbound

This paper cites Towards robust monocular depth estimation: Mixing datasets for zero-shot cross-dataset transfer.

CutS3D: Cutting Semantics in 3D for 2D Unsupervised Instance Segmentation Towards robust monocular depth estimation: Mixing datasets for zero-shot cross-dataset transfer

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T13:19:00.119009Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation f6284dd5-3dc8-4965-b9af-cfced9c8a33a · outbound

This paper cites Towards robust monocular depth estimation: Mixing datasets for zero-shot cross-dataset transfer.

CutS3D: Cutting Semantics in 3D for 2D Unsupervised Instance Segmentation Towards robust monocular depth estimation: Mixing datasets for zero-shot cross-dataset transfer

Reference 32

Resolution: unresolved; no resolver link, observed 2026-08-12T13:18:59.446189Z

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Observation f04726da-d86b-4ba0-8eed-8337f7e07f8e · outbound

This paper cites Imagenet large scale visual recognition challenge.

CutS3D: Cutting Semantics in 3D for 2D Unsupervised Instance Segmentation Imagenet large scale visual recognition challenge

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T13:19:00.083924Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 4985aab7-5dfe-4db1-9a69-9806f8215fae · outbound

This paper cites Spreading vectors for similarity search.

CutS3D: Cutting Semantics in 3D for 2D Unsupervised Instance Segmentation Spreading vectors for similarity search

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T13:19:00.047295Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 1ea9d282-97cd-4284-8fba-a879657a152e · outbound

This paper cites Leveraging hidden positives for unsupervised semantic segmentation.

CutS3D: Cutting Semantics in 3D for 2D Unsupervised Instance Segmentation Leveraging hidden positives for unsupervised semantic segmentation

Reference 35

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T13:18:59.994554Z

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Observation cb50b8b3-24c9-4dd7-931a-09629bb4432e · outbound

This paper cites Objects365: A large-scale, high-quality dataset for object detection.

CutS3D: Cutting Semantics in 3D for 2D Unsupervised Instance Segmentation Objects365: A large-scale, high-quality dataset for object detection

Reference 36

Resolution: unresolved; no resolver link, observed 2026-08-12T13:18:59.465821Z

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Unavailable: canonical work link unavailable.

Observation dc21f803-1b3e-4de1-aca7-3d30208d3e78 · outbound

This paper cites Dct-mask: Discrete cosine transform mask rep- resentation for instance segmentation.

CutS3D: Cutting Semantics in 3D for 2D Unsupervised Instance Segmentation Dct-mask: Discrete cosine transform mask rep- resentation for instance segmentation

Reference 37

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T13:18:59.968148Z

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No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 83a3f983-96b4-496e-85c3-cb34dd10a421 · outbound

This paper cites Normalized cuts and image segmentation.

CutS3D: Cutting Semantics in 3D for 2D Unsupervised Instance Segmentation Normalized cuts and image segmentation

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T13:18:59.951689Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation b86c0964-6266-4692-9191-42a63e559b34 · outbound

This paper cites Unsupervised semantic segmentation through depth-guided feature correlation and sampling.

CutS3D: Cutting Semantics in 3D for 2D Unsupervised Instance Segmentation Unsupervised semantic segmentation through depth-guided feature correlation and sampling

Reference 39

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T13:18:59.935106Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 35f4c4d6-2cac-483e-a71d-74763fe527ac · outbound

This paper cites V o, Simon Roburin, Spyros Gidaris, Andrei Bursuc, Patrick P ´erez, Renaud Mar- let, and Jean Ponce.

CutS3D: Cutting Semantics in 3D for 2D Unsupervised Instance Segmentation V o, Simon Roburin, Spyros Gidaris, Andrei Bursuc, Patrick P ´erez, Renaud Mar- let, and Jean Ponce

Reference 40

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T13:18:59.920566Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation d2d59093-78cb-443c-a0ff-a04cc91eec22 · outbound

This paper cites Kick back & relax: Learning to reconstruct the world by watching slowtv.

CutS3D: Cutting Semantics in 3D for 2D Unsupervised Instance Segmentation Kick back & relax: Learning to reconstruct the world by watching slowtv

Reference 41

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T13:18:59.905882Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 6038a8bc-918d-4e0a-9af1-b5f956347314 · outbound

This paper cites Kick Back & Relax++: Scaling Beyond Ground-Truth Depth with SlowTV & CribsTV.

CutS3D: Cutting Semantics in 3D for 2D Unsupervised Instance Segmentation Kick Back & Relax++: Scaling Beyond Ground-Truth Depth with SlowTV & CribsTV

Reference 42

Resolution: unresolved; no resolver link, observed 2026-08-12T13:18:59.493829Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3562cca1-af12-4ec2-a2f7-1a59aedd45c2 · outbound

This paper cites Discovering Object Masks with Transformers for Unsupervised Semantic Segmentation.

CutS3D: Cutting Semantics in 3D for 2D Unsupervised Instance Segmentation Discovering Object Masks with Transformers for Unsupervised Semantic Segmentation

Reference 43

Resolution: unresolved; no resolver link, observed 2026-08-12T13:18:59.499002Z

Source-reported events for the cited work

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Observation c99ca0db-1262-4d62-961b-62d4fe612dbc · outbound

This paper cites Dense contrastive learning for self-supervised visual pre-training.

CutS3D: Cutting Semantics in 3D for 2D Unsupervised Instance Segmentation Dense contrastive learning for self-supervised visual pre-training

Reference 44

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T13:18:59.890094Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation e5e7138d-78a8-4581-a272-a2629792d0e5 · outbound

This paper cites Solo: A simple framework for instance segmen- tation.

CutS3D: Cutting Semantics in 3D for 2D Unsupervised Instance Segmentation Solo: A simple framework for instance segmen- tation

Reference 45

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T13:18:59.873605Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 4292678a-a2d8-49c8-8067-c88b12e7a348 · outbound

This paper cites Freesolo: Learning to segment objects without annotations.

CutS3D: Cutting Semantics in 3D for 2D Unsupervised Instance Segmentation Freesolo: Learning to segment objects without annotations

Reference 46

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T13:18:59.856209Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 465d71f3-ebe8-420e-bcf4-2ec10e152e22 · outbound

This paper cites Cut and learn for unsupervised object detection and instance segmentation.

CutS3D: Cutting Semantics in 3D for 2D Unsupervised Instance Segmentation Cut and learn for unsupervised object detection and instance segmentation

Reference 47

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T13:18:59.838630Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 9359b1b3-50cb-4b7c-8a4c-7d732c3692c5 · outbound

This paper cites Segment anything without supervision.

CutS3D: Cutting Semantics in 3D for 2D Unsupervised Instance Segmentation Segment anything without supervision

Reference 48

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T13:18:59.820335Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 17eafadb-663b-4dba-b1a1-6860713c4d04 · outbound

This paper cites Tokencut: Segmenting objects in images and videos with self-supervised transformer and normalized cut.

CutS3D: Cutting Semantics in 3D for 2D Unsupervised Instance Segmentation Tokencut: Segmenting objects in images and videos with self-supervised transformer and normalized cut

Reference 49

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T13:18:59.802014Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 8f565721-ad46-44c9-a2b7-bc9b3d7093f6 · outbound

This paper cites Mask encoding for single shot instance seg- mentation.

CutS3D: Cutting Semantics in 3D for 2D Unsupervised Instance Segmentation Mask encoding for single shot instance seg- mentation

Reference 50

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T13:18:59.783311Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 8be3a504-c8a1-4f5d-bdab-2044784abb1c · outbound

This paper cites Image bert pre-training with online tokenizer.

CutS3D: Cutting Semantics in 3D for 2D Unsupervised Instance Segmentation Image bert pre-training with online tokenizer

Reference 51

Resolution: malformed identifier; raw_fallback, observed 2026-08-12T13:18:59.763644Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation e0dce096-0ca0-4302-9476-bb85d6db2f7e · outbound

This paper cites Overall, we observe that the CutS3D Cascade Mask R-CNN [4] is able to better differentiate instances that are connected in 2D, e.g.

CutS3D: Cutting Semantics in 3D for 2D Unsupervised Instance Segmentation Overall, we observe that the CutS3D Cascade Mask R-CNN [4] is able to better differentiate instances that are connected in 2D, e.g

Reference 52

Resolution: malformed identifier; raw_fallback, observed 2026-08-12T13:18:59.746208Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation fc39e175-8a33-4722-9c2d-f1b7ee61f281 · outbound

This paper cites †Results reproduced using the authors’ official implementation.

CutS3D: Cutting Semantics in 3D for 2D Unsupervised Instance Segmentation †Results reproduced using the authors’ official implementation

Reference 53

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T13:18:59.728207Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Coverage vector

Reference resolution

Outbound references

Pith citing papers