Paper Citation Record · LEDGER

S2CFormer: Revisiting the RD-Latency Trade-off in Transformer-based Learned Image Compression

As of 10 August 2026, this Paper Citation Record lists 58 of 58 outbound references and 1 inbound Pith citation observation for arXiv:2502.00700.

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

pith.paper-citation-record.v1
2502.00700 v3

Coverage vector

measured 58 of 58 reference resolution

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measured 59 of 59 standing notices

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measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-05-21T10:46:21.138722Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-21T10:50:01.537726Z

Reference resolution

58 of 58 outbound references displayed

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External citation measurements

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Outbound references

Observation 8c80cc19-efbb-4145-993f-3438e9f5deef · outbound

This paper cites Testimages: a large- scale archive for testing visual devices and basic image pro- cessing algorithms.

S2CFormer: Revisiting the RD-Latency Trade-off in Transformer-based Learned Image Compression Testimages: a large- scale archive for testing visual devices and basic image pro- cessing algorithms

Reference 1

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Observation a8f999a9-631a-4924-85fd-8aa22789ee6d · outbound

This paper cites End-to-end Optimized Image Compression.

S2CFormer: Revisiting the RD-Latency Trade-off in Transformer-based Learned Image Compression End-to-end Optimized Image Compression

Reference 2

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Observation 0598800e-5aed-42f9-bd4d-5aaa5d67f779 · outbound

This paper cites Variational image compression with a scale hyperprior.

S2CFormer: Revisiting the RD-Latency Trade-off in Transformer-based Learned Image Compression Variational image compression with a scale hyperprior

Reference 3

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This paper cites Compressai: a pytorch library and evaluation platform for end-to-end compression research.

S2CFormer: Revisiting the RD-Latency Trade-off in Transformer-based Learned Image Compression Compressai: a pytorch library and evaluation platform for end-to-end compression research

Reference 4

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Observation 7881d80f-0b7b-42a5-aac6-22a056ff8c9e · outbound

This paper cites Calculation of average psnr differences between rd-curves.

S2CFormer: Revisiting the RD-Latency Trade-off in Transformer-based Learned Image Compression Calculation of average psnr differences between rd-curves

Reference 5

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Observation da493452-fc3c-4862-a7d0-4add37feca8a · outbound

This paper cites Overview of the versatile video coding (vvc) standard and its applica- tions.

S2CFormer: Revisiting the RD-Latency Trade-off in Transformer-based Learned Image Compression Overview of the versatile video coding (vvc) standard and its applica- tions

Reference 6

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Observation 9abdfdad-edb8-4a99-a104-4c2deb97729d · outbound

This paper cites Browne, Y.

S2CFormer: Revisiting the RD-Latency Trade-off in Transformer-based Learned Image Compression Browne, Y

Reference 7

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Observation ada350bb-a099-4e13-83bb-237fe9f100de · outbound

This paper cites Two-stage octave residual network for end-to-end image compres- sion.

S2CFormer: Revisiting the RD-Latency Trade-off in Transformer-based Learned Image Compression Two-stage octave residual network for end-to-end image compres- sion

Reference 8

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Observation 6d045076-97fd-4de5-a08e-111e97031be4 · outbound

This paper cites Simple baselines for image restoration.

S2CFormer: Revisiting the RD-Latency Trade-off in Transformer-based Learned Image Compression Simple baselines for image restoration

Reference 9

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Observation b419c288-e220-4270-85ec-1baec95799af · outbound

This paper cites Learned image compression with discretized gaussian mixture likelihoods and attention modules.

S2CFormer: Revisiting the RD-Latency Trade-off in Transformer-based Learned Image Compression Learned image compression with discretized gaussian mixture likelihoods and attention modules

Reference 10

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Observation 4ebcb032-e33c-49ef-a543-5a30532f24ca · outbound

This paper cites Xception: Deep learning with depth- wise separable convolutions.

S2CFormer: Revisiting the RD-Latency Trade-off in Transformer-based Learned Image Compression Xception: Deep learning with depth- wise separable convolutions

Reference 11

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This paper cites Workshop and challenge on learned image com- pression.

S2CFormer: Revisiting the RD-Latency Trade-off in Transformer-based Learned Image Compression Workshop and challenge on learned image com- pression

Reference 12

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This paper cites Language modeling with gated convolutional networks.

S2CFormer: Revisiting the RD-Latency Trade-off in Transformer-based Learned Image Compression Language modeling with gated convolutional networks

Reference 13

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Observation 31e60e1f-c9b2-41c8-b4c7-0ff7ff9fd64f · outbound

This paper cites Cswin transformer: A general vision transformer backbone with cross-shaped windows.

S2CFormer: Revisiting the RD-Latency Trade-off in Transformer-based Learned Image Compression Cswin transformer: A general vision transformer backbone with cross-shaped windows

Reference 14

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Observation 5c8f9403-746b-4213-b39f-8b4ebf1b0a53 · outbound

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

S2CFormer: Revisiting the RD-Latency Trade-off in Transformer-based Learned Image Compression An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale

Reference 15

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Observation 86b4268a-9d5e-48fc-9375-197c4706449d · outbound

This paper cites Asymmetric learned image com- pression with multi-scale residual block, importance scal- ing, and post-quantization filtering.

S2CFormer: Revisiting the RD-Latency Trade-off in Transformer-based Learned Image Compression Asymmetric learned image com- pression with multi-scale residual block, importance scal- ing, and post-quantization filtering

Reference 16

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Observation a310faf6-741b-4008-909c-640180c2edf0 · outbound

This paper cites Neural image compression via attentional multi-scale back projection and frequency de- composition.

S2CFormer: Revisiting the RD-Latency Trade-off in Transformer-based Learned Image Compression Neural image compression via attentional multi-scale back projection and frequency de- composition

Reference 17

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Observation e575881d-a3b9-4d1b-b0f1-b8902eea1439 · outbound

This paper cites Causal context adjustment loss for learned image compression.

S2CFormer: Revisiting the RD-Latency Trade-off in Transformer-based Learned Image Compression Causal context adjustment loss for learned image compression

Reference 18

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This paper cites S4d: Streaming 4d real-world reconstruction with gaussians and 3d control points.

S2CFormer: Revisiting the RD-Latency Trade-off in Transformer-based Learned Image Compression S4d: Streaming 4d real-world reconstruction with gaussians and 3d control points

Reference 19

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Observation f32f78a3-d089-4a45-84dc-02a9aa29b3da · outbound

This paper cites Checkerboard context model for efficient learned image compression.

S2CFormer: Revisiting the RD-Latency Trade-off in Transformer-based Learned Image Compression Checkerboard context model for efficient learned image compression

Reference 20

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Observation 44afa33f-a9e2-49d1-9a0d-ef158c451539 · outbound

This paper cites Elic: Efficient learned image compres- sion with unevenly grouped space-channel contextual adap- tive coding.

S2CFormer: Revisiting the RD-Latency Trade-off in Transformer-based Learned Image Compression Elic: Efficient learned image compres- sion with unevenly grouped space-channel contextual adap- tive coding

Reference 21

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Observation ad47bcbd-4f6d-4627-a23b-bce867f9d9bd · outbound

This paper cites MLIC$^{++}$: Linear com- plexity multi-reference entropy modeling for learned image compression.

S2CFormer: Revisiting the RD-Latency Trade-off in Transformer-based Learned Image Compression MLIC$^{++}$: Linear com- plexity multi-reference entropy modeling for learned image compression

Reference 22

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Observation 924b0852-3abc-4bbf-be10-4af1c84ae1c6 · outbound

This paper cites Mlic: Multi-reference entropy model for learned image compression.

S2CFormer: Revisiting the RD-Latency Trade-off in Transformer-based Learned Image Compression Mlic: Multi-reference entropy model for learned image compression

Reference 23

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This paper cites Adam: A Method for Stochastic Optimization.

S2CFormer: Revisiting the RD-Latency Trade-off in Transformer-based Learned Image Compression Adam: A Method for Stochastic Optimization

Reference 24

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Observation c2e056d3-13a8-45b3-8ab9-017aa99261a7 · outbound

This paper cites Kodak lossless true color im- age suite (photocd pcd0992), 1993.

S2CFormer: Revisiting the RD-Latency Trade-off in Transformer-based Learned Image Compression Kodak lossless true color im- age suite (photocd pcd0992), 1993

Reference 25

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Observation 23eeba52-dcb0-40f1-b630-76816dce48f0 · outbound

This paper cites Con- textformer: A transformer with spatio-channel attention for context modeling in learned image compression.

S2CFormer: Revisiting the RD-Latency Trade-off in Transformer-based Learned Image Compression Con- textformer: A transformer with spatio-channel attention for context modeling in learned image compression

Reference 26

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This paper cites FNet: Mixing Tokens with Fourier Transforms.

S2CFormer: Revisiting the RD-Latency Trade-off in Transformer-based Learned Image Compression FNet: Mixing Tokens with Fourier Transforms

Reference 27

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Observation f082d866-eacd-4a43-9e7e-777b79ae1ecf · outbound

This paper cites Frequency-Aware Transformer for Learned Image Compression.

S2CFormer: Revisiting the RD-Latency Trade-off in Transformer-based Learned Image Compression Frequency-Aware Transformer for Learned Image Compression

Reference 28

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Observation 64cd2929-471c-4dc3-b9e3-2d50d4b05916 · outbound

This paper cites Hybrid spatial-temporal en- tropy modelling for neural video compression.

S2CFormer: Revisiting the RD-Latency Trade-off in Transformer-based Learned Image Compression Hybrid spatial-temporal en- tropy modelling for neural video compression

Reference 29

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Observation 1eb388bf-17bc-475f-bd80-462fd1cbe92d · outbound

This paper cites Neural video compression with diverse contexts.

S2CFormer: Revisiting the RD-Latency Trade-off in Transformer-based Learned Image Compression Neural video compression with diverse contexts

Reference 30

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Observation 8f1168da-2518-40ef-9aa9-1deb02ec5768 · outbound

This paper cites Swinir: Image restoration using swin transformer.

S2CFormer: Revisiting the RD-Latency Trade-off in Transformer-based Learned Image Compression Swinir: Image restoration using swin transformer

Reference 31

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Observation b3217583-dee4-49a7-80bb-8a61b82e50d6 · outbound

This paper cites A Unified End-to-End Framework for Efficient Deep Image Compression.

S2CFormer: Revisiting the RD-Latency Trade-off in Transformer-based Learned Image Compression A Unified End-to-End Framework for Efficient Deep Image Compression

Reference 32

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Observation b5de1da3-a622-4169-a7c7-abf09169f69b · outbound

This paper cites Learned im- age compression with mixed transformer-cnn architectures.

S2CFormer: Revisiting the RD-Latency Trade-off in Transformer-based Learned Image Compression Learned im- age compression with mixed transformer-cnn architectures

Reference 33

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

S2CFormer: Revisiting the RD-Latency Trade-off in Transformer-based Learned Image Compression Swin transformer: Hierarchical vision transformer using shifted windows

Reference 34

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This paper cites Swin transformer v2: Scaling up capacity and resolution.

S2CFormer: Revisiting the RD-Latency Trade-off in Transformer-based Learned Image Compression Swin transformer v2: Scaling up capacity and resolution

Reference 35

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This paper cites Transformer-based image compression.

S2CFormer: Revisiting the RD-Latency Trade-off in Transformer-based Learned Image Compression Transformer-based image compression

Reference 36

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This paper cites Understanding the effective receptive field in deep convo- lutional neural networks.

S2CFormer: Revisiting the RD-Latency Trade-off in Transformer-based Learned Image Compression Understanding the effective receptive field in deep convo- lutional neural networks

Reference 37

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Observation 9a1a6ecc-221e-4b4d-8ca0-f58bf58fbb6c · outbound

This paper cites iwave: Cnn-based wavelet-like transform for image compression.

S2CFormer: Revisiting the RD-Latency Trade-off in Transformer-based Learned Image Compression iwave: Cnn-based wavelet-like transform for image compression

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T18:05:28.401655Z

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Observation 3411c965-a360-46c7-b5bc-fd5bf19b406a · outbound

This paper cites End-to-end optimized versatile image compression with wavelet-like transform.

S2CFormer: Revisiting the RD-Latency Trade-off in Transformer-based Learned Image Compression End-to-end optimized versatile image compression with wavelet-like transform

Reference 39

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T18:05:28.387188Z

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Observation ef76807d-6c10-4db6-b168-cc997d8b7101 · outbound

This paper cites VCT: A Video Compression Transformer.

S2CFormer: Revisiting the RD-Latency Trade-off in Transformer-based Learned Image Compression VCT: A Video Compression Transformer

Reference 40

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Observation 07a08c51-1984-4bf9-b16b-b2d20dbc06c5 · outbound

This paper cites Channel-wise autoregres- sive entropy models for learned image compression.

S2CFormer: Revisiting the RD-Latency Trade-off in Transformer-based Learned Image Compression Channel-wise autoregres- sive entropy models for learned image compression

Reference 41

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T18:05:28.370916Z

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Observation b50574cd-7951-4765-9658-860bf66785ad · outbound

This paper cites Joint autoregressive and hierarchical priors for learned im- age compression.

S2CFormer: Revisiting the RD-Latency Trade-off in Transformer-based Learned Image Compression Joint autoregressive and hierarchical priors for learned im- age compression

Reference 42

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T18:05:28.356667Z

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Observation a6dc7549-ea9a-491a-87e3-5a68896e5512 · outbound

This paper cites Entroformer: A Transformer-based Entropy Model for Learned Image Compression.

S2CFormer: Revisiting the RD-Latency Trade-off in Transformer-based Learned Image Compression Entroformer: A Transformer-based Entropy Model for Learned Image Compression

Reference 43

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Observation 6eb7e687-678c-4464-ac87-0d0fac05e233 · outbound

This paper cites MambaVC: Learned Visual Compression with Selective State Spaces.

S2CFormer: Revisiting the RD-Latency Trade-off in Transformer-based Learned Image Compression MambaVC: Learned Visual Compression with Selective State Spaces

Reference 44

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Observation ce40436c-7508-40fc-ae6c-8e4915f8a2d3 · outbound

This paper cites Bayesian neural networks avoid encoding com- plex and perturbation-sensitive concepts.

S2CFormer: Revisiting the RD-Latency Trade-off in Transformer-based Learned Image Compression Bayesian neural networks avoid encoding com- plex and perturbation-sensitive concepts

Reference 45

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T18:05:28.342075Z

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Observation 8a13e6c4-d356-427c-8ba6-552bc5d5f55a · outbound

This paper cites Mobilenetv2: Inverted residuals and linear bottlenecks.

S2CFormer: Revisiting the RD-Latency Trade-off in Transformer-based Learned Image Compression Mobilenetv2: Inverted residuals and linear bottlenecks

Reference 46

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T18:05:28.327939Z

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Observation e2d3c1fc-30ae-479f-9241-d55e6b43ea91 · outbound

This paper cites Training data-efficient image transformers & distillation through atten- tion.

S2CFormer: Revisiting the RD-Latency Trade-off in Transformer-based Learned Image Compression Training data-efficient image transformers & distillation through atten- tion

Reference 47

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T18:05:28.314033Z

Source-reported events for the cited work

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This paper cites Attention is all you need.

S2CFormer: Revisiting the RD-Latency Trade-off in Transformer-based Learned Image Compression Attention is all you need

Reference 48

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This paper cites Vision transformer with deformable attention.

S2CFormer: Revisiting the RD-Latency Trade-off in Transformer-based Learned Image Compression Vision transformer with deformable attention

Reference 49

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Observation 17a79e18-614f-4896-8122-bae99b361cbc · outbound

This paper cites Enhanced invertible encoding for learned image compression.

S2CFormer: Revisiting the RD-Latency Trade-off in Transformer-based Learned Image Compression Enhanced invertible encoding for learned image compression

Reference 50

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T18:05:28.274700Z

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Observation d4834d6a-ee30-46d7-ab81-1d0cc859ff23 · outbound

This paper cites Metaformer is actually what you need for vision.

S2CFormer: Revisiting the RD-Latency Trade-off in Transformer-based Learned Image Compression Metaformer is actually what you need for vision

Reference 51

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T18:05:28.258323Z

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Observation 6986612c-1ed1-42a6-a4dd-df6568ea6a48 · outbound

This paper cites Metaformer baselines for vision.

S2CFormer: Revisiting the RD-Latency Trade-off in Transformer-based Learned Image Compression Metaformer baselines for vision

Reference 52

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T18:05:28.242723Z

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Observation 7e69885b-6815-4a62-97b7-9b5bc3dc1703 · outbound

This paper cites Frequency disentangled features in 10 neural image compression.

S2CFormer: Revisiting the RD-Latency Trade-off in Transformer-based Learned Image Compression Frequency disentangled features in 10 neural image compression

Reference 53

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T18:05:28.227877Z

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Observation f2169e34-67be-46d1-82d0-76316e644b2b · outbound

This paper cites Restormer: Efficient transformer for high-resolution image restoration.

S2CFormer: Revisiting the RD-Latency Trade-off in Transformer-based Learned Image Compression Restormer: Efficient transformer for high-resolution image restoration

Reference 54

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This paper cites Practical blind denoising via swin-conv-unet and data synthesis.

S2CFormer: Revisiting the RD-Latency Trade-off in Transformer-based Learned Image Compression Practical blind denoising via swin-conv-unet and data synthesis

Reference 55

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T18:05:28.204795Z

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Observation cfe3f9d7-6b92-4ced-b1a2-2ef859730585 · outbound

This paper cites Neural rate control for learned video compression.

S2CFormer: Revisiting the RD-Latency Trade-off in Transformer-based Learned Image Compression Neural rate control for learned video compression

Reference 56

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T18:05:28.189754Z

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Observation 588eef0f-ef55-4d09-97d6-33b18e475851 · outbound

This paper cites Transformer-based transform coding.

S2CFormer: Revisiting the RD-Latency Trade-off in Transformer-based Learned Image Compression Transformer-based transform coding

Reference 57

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T18:05:28.174740Z

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Observation 5ae4e721-f41b-4da9-9ed9-1d7fc95011ef · outbound

This paper cites The devil is in the details: Window-based attention for image compression.

S2CFormer: Revisiting the RD-Latency Trade-off in Transformer-based Learned Image Compression The devil is in the details: Window-based attention for image compression

Reference 58

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T18:05:28.158880Z

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Pith citing papers

Observation ad8c8e30-9c8a-4faa-b5ee-98a25d5209f6 · inbound

Inevitable Encounters: Backdoor Attacks Involving Lossy Compression cites this paper.

Inevitable Encounters: Backdoor Attacks Involving Lossy Compression S2CFormer: Revisiting the RD-Latency Trade-off in Transformer-based Learned Image Compression

Reference 38

Resolution: verified exact; arxiv_id, observed 2026-05-21T10:50:01.539547Z

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