Paper Citation Record · LEDGER

Hadamard Attention Recurrent Transformer: A Strong Baseline for Stereo Matching Transformer

As of 14 August 2026, this Paper Citation Record lists 55 of 55 outbound references and 2 inbound Pith citation observations for arXiv:2501.01023.

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

pith.paper-citation-record.v1
2501.01023 v5

Coverage vector

measured 55 of 55 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-10T22:41:02.793094Z

measured 57 of 57 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-14T06:32:32.682623+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-12T17:38:44.067412Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-12T17:38:44.674866Z

Reference resolution

55 of 55 outbound references displayed

verified exact0
verified fuzzy51
unresolved4
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation f59c630c-15d9-4f9c-a9d9-cd92c8bad31c · outbound

This paper cites Surface depth estimation from multi-view stereo satellite images with distribution contrast network.

Hadamard Attention Recurrent Transformer: A Strong Baseline for Stereo Matching Transformer Surface depth estimation from multi-view stereo satellite images with distribution contrast network

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:41:03.679862Z

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Observation 83faf0c1-5683-4eee-88f2-13ece1c51b38 · outbound

This paper cites Prior information guided semi-supervised semantic segmentation of remote sensing images.

Hadamard Attention Recurrent Transformer: A Strong Baseline for Stereo Matching Transformer Prior information guided semi-supervised semantic segmentation of remote sensing images

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:41:03.664655Z

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Observation 8050f6cd-be8f-4d2d-9b13-4ec7e5342268 · outbound

This paper cites Rethinking low-light knowledge for pedestrian detection in nighttime conditions.

Hadamard Attention Recurrent Transformer: A Strong Baseline for Stereo Matching Transformer Rethinking low-light knowledge for pedestrian detection in nighttime conditions

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:41:03.648329Z

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Observation 2d2c39a3-3296-4cfd-9ca3-6f8f96b788e0 · outbound

This paper cites Raft-stereo: Multilevel recurrent field transforms for stereo matching.

Hadamard Attention Recurrent Transformer: A Strong Baseline for Stereo Matching Transformer Raft-stereo: Multilevel recurrent field transforms for stereo matching

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:41:03.633667Z

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Observation c871b8e9-61f5-41ec-809f-77bacddce5bf · outbound

This paper cites Iterative geometry encoding volume for stereo matching.

Hadamard Attention Recurrent Transformer: A Strong Baseline for Stereo Matching Transformer Iterative geometry encoding volume for stereo matching

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:41:03.618124Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 5b116644-724d-4216-8896-cfa6135e49f0 · outbound

This paper cites Mocha-stereo: Motif channel attention network for stereo matching.

Hadamard Attention Recurrent Transformer: A Strong Baseline for Stereo Matching Transformer Mocha-stereo: Motif channel attention network for stereo matching

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:41:03.602831Z

Source-reported events for the cited work

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Observation 4a63bd2d-652a-4cd9-b262-26970a15dbff · outbound

This paper cites Revisiting stereo depth estimation from a sequence-to-sequence perspective with transformers.

Hadamard Attention Recurrent Transformer: A Strong Baseline for Stereo Matching Transformer Revisiting stereo depth estimation from a sequence-to-sequence perspective with transformers

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:41:03.586822Z

Source-reported events for the cited work

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Observation ad02de44-fa09-4544-a27d-4cb3f2661304 · outbound

This paper cites Elfnet: Evidential local-global fusion for stereo matching.

Hadamard Attention Recurrent Transformer: A Strong Baseline for Stereo Matching Transformer Elfnet: Evidential local-global fusion for stereo matching

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:41:03.572422Z

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Observation bda3c7a1-a57e-4ef2-ae2c-bcada19eb68e · outbound

This paper cites Low-rank bottleneck in multi-head attention models.

Hadamard Attention Recurrent Transformer: A Strong Baseline for Stereo Matching Transformer Low-rank bottleneck in multi-head attention models

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:41:03.555846Z

Source-reported events for the cited work

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Observation fa673fd2-d0a7-4f28-be4c-45e9cd8661d5 · outbound

This paper cites Group-wise correlation stereo network.

Hadamard Attention Recurrent Transformer: A Strong Baseline for Stereo Matching Transformer Group-wise correlation stereo network

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:41:03.539368Z

Source-reported events for the cited work

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Observation aa5dffc0-fb1f-4bba-bc8e-305abb94d54e · outbound

This paper cites Feature distribution normalization network for multi-view stereo.

Hadamard Attention Recurrent Transformer: A Strong Baseline for Stereo Matching Transformer Feature distribution normalization network for multi-view stereo

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:41:03.521698Z

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Observation 1c459648-1820-46f6-8be3-c9b30a063bdd · outbound

This paper cites Practical stereo matching via cascaded recurrent network with adaptive correlation.

Hadamard Attention Recurrent Transformer: A Strong Baseline for Stereo Matching Transformer Practical stereo matching via cascaded recurrent network with adaptive correlation

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:41:03.504727Z

Source-reported events for the cited work

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Observation 54c4aec8-944a-47ae-9f36-012e23f5f83e · outbound

This paper cites Leveraging negative correlation for full-range self-attention in vision transformers.

Hadamard Attention Recurrent Transformer: A Strong Baseline for Stereo Matching Transformer Leveraging negative correlation for full-range self-attention in vision transformers

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:41:03.488183Z

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Observation 50ff77dd-6cc6-4f9c-a359-03044bd375ce · outbound

This paper cites Croco v2: Improved cross-view completion pre-training for stereo matching and optical flow.

Hadamard Attention Recurrent Transformer: A Strong Baseline for Stereo Matching Transformer Croco v2: Improved cross-view completion pre-training for stereo matching and optical flow

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:41:03.473941Z

Source-reported events for the cited work

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Observation 4d5f681a-37bc-45f6-8add-3d1cf27a5416 · outbound

This paper cites A frequency-domain dynamic amplitude filtering method for single-image dehazing with harmony enhancement.

Hadamard Attention Recurrent Transformer: A Strong Baseline for Stereo Matching Transformer A frequency-domain dynamic amplitude filtering method for single-image dehazing with harmony enhancement

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:41:03.459603Z

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Observation b775bb49-473a-4b14-b370-4644313cb98e · outbound

This paper cites High-frequency stereo matching network.

Hadamard Attention Recurrent Transformer: A Strong Baseline for Stereo Matching Transformer High-frequency stereo matching network

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:41:03.444277Z

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Observation 073ea6fe-19f7-470e-b438-8cac335f511b · outbound

This paper cites Retinastereo: Dynamic- volume stereo matching network.

Hadamard Attention Recurrent Transformer: A Strong Baseline for Stereo Matching Transformer Retinastereo: Dynamic- volume stereo matching network

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:41:03.427394Z

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Observation 981d9362-862e-47c0-8611-be42886ded3b · outbound

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

Hadamard Attention Recurrent Transformer: A Strong Baseline for Stereo Matching Transformer Restormer: E fficient transformer for high-resolution image restoration

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:41:03.409815Z

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Observation b8d991e0-5112-49d2-8cce-22b2351a644f · outbound

This paper cites Catnet: Coordinate-aware transformer for all-in-one image restoration.

Hadamard Attention Recurrent Transformer: A Strong Baseline for Stereo Matching Transformer Catnet: Coordinate-aware transformer for all-in-one image restoration

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:41:03.394499Z

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Observation 727af695-b581-4a79-96dc-5314dfdab5ae · outbound

This paper cites Attention is all you need.

Hadamard Attention Recurrent Transformer: A Strong Baseline for Stereo Matching Transformer Attention is all you need

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:41:03.379297Z

Source-reported events for the cited work

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Observation 343f374c-3483-4e1a-bb40-506cd9566277 · outbound

This paper cites Linformer: Self-Attention with Linear Complexity.

Hadamard Attention Recurrent Transformer: A Strong Baseline for Stereo Matching Transformer Linformer: Self-Attention with Linear Complexity

Reference 21

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Observation 77631dad-79fa-4509-9d4d-02b3876010ec · outbound

This paper cites E fficient attention: Attention with linear complexities.

Hadamard Attention Recurrent Transformer: A Strong Baseline for Stereo Matching Transformer E fficient attention: Attention with linear complexities

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:41:03.365869Z

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Observation 8d7ebd80-e55c-4eab-a5e3-2e6c84ad7775 · outbound

This paper cites Attention is not all you need: Pure attention loses rank doubly exponentially with depth.

Hadamard Attention Recurrent Transformer: A Strong Baseline for Stereo Matching Transformer Attention is not all you need: Pure attention loses rank doubly exponentially with depth

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:41:03.351560Z

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Observation 2b64f209-cfd8-4f31-a13d-0c3231203caf · outbound

This paper cites Deep residual learning for image recognition.

Hadamard Attention Recurrent Transformer: A Strong Baseline for Stereo Matching Transformer Deep residual learning for image recognition

Reference 24

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Observation 628d92b6-8399-4f3c-bb50-ac3e079f209f · outbound

This paper cites Visualizing and understanding convolutional networks.

Hadamard Attention Recurrent Transformer: A Strong Baseline for Stereo Matching Transformer Visualizing and understanding convolutional networks

Reference 25

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Observation f454ca9d-e26b-4d75-9544-43ef8dd521cf · outbound

This paper cites Large kernel matters–improve semantic segmentation by global convo- lutional network.

Hadamard Attention Recurrent Transformer: A Strong Baseline for Stereo Matching Transformer Large kernel matters–improve semantic segmentation by global convo- lutional network

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:41:03.308944Z

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Observation e58f069f-cfd7-466a-b367-da6e0f587683 · outbound

This paper cites Hornet: Efficient high-order spatial interactions with recursive gated convolutions.

Hadamard Attention Recurrent Transformer: A Strong Baseline for Stereo Matching Transformer Hornet: Efficient high-order spatial interactions with recursive gated convolutions

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:41:03.293403Z

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Observation 58bfe1cd-dfc2-4d8c-9a5d-48ae5c0af28e · outbound

This paper cites Layer Normalization.

Hadamard Attention Recurrent Transformer: A Strong Baseline for Stereo Matching Transformer Layer Normalization

Reference 28

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Observation 89aeaed5-6996-434f-a4f9-26feb6b20ee3 · outbound

This paper cites Motif Channel Opened in a White-Box: Stereo Matching via Motif Correlation Graph.

Hadamard Attention Recurrent Transformer: A Strong Baseline for Stereo Matching Transformer Motif Channel Opened in a White-Box: Stereo Matching via Motif Correlation Graph

Reference 29

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Observation 43a8ec8f-b16e-41fa-a064-51b9c5666d13 · outbound

This paper cites E fficientnet: Rethinking model scaling for convolutional neural networks.

Hadamard Attention Recurrent Transformer: A Strong Baseline for Stereo Matching Transformer E fficientnet: Rethinking model scaling for convolutional neural networks

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:41:03.276735Z

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Observation 8fbf7a91-b22a-459d-8d9b-f5f44e3f6382 · outbound

This paper cites Are we ready for autonomous driving? the kitti vision benchmark suite.

Hadamard Attention Recurrent Transformer: A Strong Baseline for Stereo Matching Transformer Are we ready for autonomous driving? the kitti vision benchmark suite

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:41:03.262608Z

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Observation 0a195308-6dba-4a64-9a44-22b90c4aceed · outbound

This paper cites Object scene flow for autonomous vehicles.

Hadamard Attention Recurrent Transformer: A Strong Baseline for Stereo Matching Transformer Object scene flow for autonomous vehicles

Reference 32

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Observation ff9ccdf4-7860-45e6-82b1-74d10c20fded · outbound

This paper cites A large dataset to train convolutional networks for disparity, optical flow, and scene flow estimation.

Hadamard Attention Recurrent Transformer: A Strong Baseline for Stereo Matching Transformer A large dataset to train convolutional networks for disparity, optical flow, and scene flow estimation

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:41:03.229204Z

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Observation dac8eeac-fc6a-44d5-9a1f-b783cec9f018 · outbound

This paper cites High-resolution stereo datasets with subpixel-accurate ground truth.

Hadamard Attention Recurrent Transformer: A Strong Baseline for Stereo Matching Transformer High-resolution stereo datasets with subpixel-accurate ground truth

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:41:03.209788Z

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Observation cfeedada-839a-43e1-9bc7-e78857dadcc7 · outbound

This paper cites Tartanair: A dataset to push the limits of visual slam.

Hadamard Attention Recurrent Transformer: A Strong Baseline for Stereo Matching Transformer Tartanair: A dataset to push the limits of visual slam

Reference 35

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:41:03.193752Z

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Observation 8c6008d1-186b-477d-9e1b-4cdede1e8a1d · outbound

This paper cites Falling things: A synthetic dataset for 3d object detection and pose estimation.

Hadamard Attention Recurrent Transformer: A Strong Baseline for Stereo Matching Transformer Falling things: A synthetic dataset for 3d object detection and pose estimation

Reference 36

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:41:03.179855Z

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Observation d66baaf8-08b2-440c-85b4-84009eb7da66 · outbound

This paper cites Instereo2k: a large real dataset for stereo matching in indoor scenes.

Hadamard Attention Recurrent Transformer: A Strong Baseline for Stereo Matching Transformer Instereo2k: a large real dataset for stereo matching in indoor scenes

Reference 37

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:41:03.164510Z

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Observation 7302453d-0126-47d6-9c31-a3b25f617a48 · outbound

This paper cites Hierarchical deep stereo matching on high-resolution images.

Hadamard Attention Recurrent Transformer: A Strong Baseline for Stereo Matching Transformer Hierarchical deep stereo matching on high-resolution images

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:41:03.148582Z

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Observation 3b2894bc-e49e-4f09-8a5e-2ac191d3e3bd · outbound

This paper cites End-to-end learning of geometry and context for deep stereo regression.

Hadamard Attention Recurrent Transformer: A Strong Baseline for Stereo Matching Transformer End-to-end learning of geometry and context for deep stereo regression

Reference 39

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:41:03.132888Z

Source-reported events for the cited work

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Observation 716eb84b-9d49-4cd3-8939-1f6682661097 · outbound

This paper cites Ga-net: Guided aggregation net for end-to-end stereo matching.

Hadamard Attention Recurrent Transformer: A Strong Baseline for Stereo Matching Transformer Ga-net: Guided aggregation net for end-to-end stereo matching

Reference 40

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:41:03.116466Z

Source-reported events for the cited work

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Observation 77ceca95-07ff-4d54-9613-5630191b4f24 · outbound

This paper cites Aanet: Adaptive aggregation network for efficient stereo matching.

Hadamard Attention Recurrent Transformer: A Strong Baseline for Stereo Matching Transformer Aanet: Adaptive aggregation network for efficient stereo matching

Reference 41

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:41:03.099748Z

Source-reported events for the cited work

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Observation 45eb9e67-fa3f-4415-a13f-07ff9d53b871 · outbound

This paper cites Accurate and efficient stereo matching via attention concatenation volume.

Hadamard Attention Recurrent Transformer: A Strong Baseline for Stereo Matching Transformer Accurate and efficient stereo matching via attention concatenation volume

Reference 42

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:41:03.084097Z

Source-reported events for the cited work

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Observation 46182e0a-f3ba-44fa-8f2d-aeb34ee682e9 · outbound

This paper cites Selective-stereo: Adaptive frequency information selection for stereo matching.

Hadamard Attention Recurrent Transformer: A Strong Baseline for Stereo Matching Transformer Selective-stereo: Adaptive frequency information selection for stereo matching

Reference 43

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:41:03.069268Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation f618fa7b-4393-4d26-8e9a-c2211118e799 · outbound

This paper cites Global occlusion-aware transformer for robust stereo matching.

Hadamard Attention Recurrent Transformer: A Strong Baseline for Stereo Matching Transformer Global occlusion-aware transformer for robust stereo matching

Reference 44

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:41:03.055211Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 7b0475ec-6294-4c43-84fc-d10909a07a63 · outbound

This paper cites P3snet: Parallel pyramid pooling stereo network.

Hadamard Attention Recurrent Transformer: A Strong Baseline for Stereo Matching Transformer P3snet: Parallel pyramid pooling stereo network

Reference 45

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:41:03.041472Z

Source-reported events for the cited work

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Observation 8dc81b98-78b5-4fc8-aa7e-3e2f69b1b41d · outbound

This paper cites Digging into uncertainty-based pseudo-label for robust stereo matching.

Hadamard Attention Recurrent Transformer: A Strong Baseline for Stereo Matching Transformer Digging into uncertainty-based pseudo-label for robust stereo matching

Reference 46

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:41:03.024832Z

Source-reported events for the cited work

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Observation 78740ad5-8efd-4d4c-a32b-dc9e38a0f2aa · outbound

This paper cites Adaptive multi-modal cross-entropy loss for stereo matching.

Hadamard Attention Recurrent Transformer: A Strong Baseline for Stereo Matching Transformer Adaptive multi-modal cross-entropy loss for stereo matching

Reference 47

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:41:03.008262Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 16eb7c41-88d7-41fb-a472-a64c52ccd202 · outbound

This paper cites Los: Local structure-guided stereo matching.

Hadamard Attention Recurrent Transformer: A Strong Baseline for Stereo Matching Transformer Los: Local structure-guided stereo matching

Reference 48

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:41:02.993706Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 4f381c68-89b8-4436-b8dc-e44ea00f58d0 · outbound

This paper cites Adstereo: Efficient stereo matching with adaptive downsampling and disparity alignment.

Hadamard Attention Recurrent Transformer: A Strong Baseline for Stereo Matching Transformer Adstereo: Efficient stereo matching with adaptive downsampling and disparity alignment

Reference 49

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:41:02.979139Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation c9645e44-afb0-4d4e-8b26-2fb9e4272266 · outbound

This paper cites Any-stereo: Arbitrary scale disparity estimation for iterative stereo matching.

Hadamard Attention Recurrent Transformer: A Strong Baseline for Stereo Matching Transformer Any-stereo: Arbitrary scale disparity estimation for iterative stereo matching

Reference 50

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:41:02.963837Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 84626a3c-a65e-4c99-b185-ae83de602072 · outbound

This paper cites Robust synthetic-to-real transfer for stereo matching.

Hadamard Attention Recurrent Transformer: A Strong Baseline for Stereo Matching Transformer Robust synthetic-to-real transfer for stereo matching

Reference 51

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:41:02.947452Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 5d2ed011-8d93-4455-850c-cbe70cc9b3ce · outbound

This paper cites A transformer-based architecture for high-resolution stereo matching.IEEE Trans.

Hadamard Attention Recurrent Transformer: A Strong Baseline for Stereo Matching Transformer A transformer-based architecture for high-resolution stereo matching.IEEE Trans

Reference 52

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:41:02.932202Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation b60e5e20-d9f7-4b4f-8a11-c72eed035032 · outbound

This paper cites Context-enhanced stereo transformer.

Hadamard Attention Recurrent Transformer: A Strong Baseline for Stereo Matching Transformer Context-enhanced stereo transformer

Reference 53

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:41:02.914749Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 3d1abea3-7c31-479c-bfdf-32db12c31243 · outbound

This paper cites Cfnet: Cascade and fused cost volume for robust stereo matching.

Hadamard Attention Recurrent Transformer: A Strong Baseline for Stereo Matching Transformer Cfnet: Cascade and fused cost volume for robust stereo matching

Reference 54

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:41:02.897614Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 79dd5722-b9cc-47ca-a279-a5b91013a1e7 · outbound

This paper cites Drivingstereo: A large-scale dataset for stereo matching in autonomous driving scenarios.

Hadamard Attention Recurrent Transformer: A Strong Baseline for Stereo Matching Transformer Drivingstereo: A large-scale dataset for stereo matching in autonomous driving scenarios

Reference 55

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:41:02.882615Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Pith citing papers

Observation cf4a8479-ad53-48b2-b8dd-1773fac5363d · inbound

Motif Channel Opened in a White-Box: Stereo Matching via Motif Correlation Graph cites this paper.

Motif Channel Opened in a White-Box: Stereo Matching via Motif Correlation Graph Hadamard Attention Recurrent Transformer: A Strong Baseline for Stereo Matching Transformer

Reference 60

Resolution: verified exact; local_arxiv, observed 2026-08-12T17:38:44.759731Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 3782bf93-62bf-4111-95a8-a2bebbdf0283 · inbound

WHTMix: Efficient Stereo Depth Estimation via Walsh-Hadamard Token Mixing cites this paper.

WHTMix: Efficient Stereo Depth Estimation via Walsh-Hadamard Token Mixing Hadamard Attention Recurrent Transformer: A Strong Baseline for Stereo Matching Transformer

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-01T03:05:45.577578Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.