STEREOFLOW: Progressive Stereo Matching with StereoDiT and Transition Flow Matching | Paper Citation Record

Observation 01106225-8602-4950-a90e-ccafa6a97c95 · outbound

This paper cites A taxonomy and evaluation of dense two-frame stereo correspondence algorithms,.

STEREOFLOW: Progressive Stereo Matching with StereoDiT and Transition Flow Matching A taxonomy and evaluation of dense two-frame stereo correspondence algorithms,

Reference 1

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Observation 67ec38df-2d5b-4833-a2ef-bf1476dbe68f · outbound

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

STEREOFLOW: Progressive Stereo Matching with StereoDiT and Transition Flow Matching Are we ready for autonomous driving? the KITTI vision benchmark suite,

Reference 2

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Observation 4adadce3-e4c5-401c-9204-ad7bd2ec9168 · outbound

This paper cites Stereo matching in time: 100+ FPS video stereo matching for extended reality,.

STEREOFLOW: Progressive Stereo Matching with StereoDiT and Transition Flow Matching Stereo matching in time: 100+ FPS video stereo matching for extended reality,

Reference 3

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Observation dd247592-8710-4bfe-a555-809062deeccf · outbound

This paper cites Object scene flow for autonomous vehicles,.

STEREOFLOW: Progressive Stereo Matching with StereoDiT and Transition Flow Matching Object scene flow for autonomous vehicles,

Reference 4

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This paper cites A multi-view stereo benchmark with high-resolution images and multi-camera videos,.

STEREOFLOW: Progressive Stereo Matching with StereoDiT and Transition Flow Matching A multi-view stereo benchmark with high-resolution images and multi-camera videos,

Reference 5

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Observation 2b3656bb-65bc-4303-a7d7-d9d1ab5b33a6 · outbound

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

STEREOFLOW: Progressive Stereo Matching with StereoDiT and Transition Flow Matching High-resolution stereo datasets with subpixel-accurate ground truth,

Reference 6

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Observation eb9ceccd-e798-446b-bc2b-3ef4a393cef0 · outbound

This paper cites Iterative geometry encoding volume for stereo matching,.

STEREOFLOW: Progressive Stereo Matching with StereoDiT and Transition Flow Matching Iterative geometry encoding volume for stereo matching,

Reference 7

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This paper cites Defom-stereo: Depth foundation model based stereo matching,.

STEREOFLOW: Progressive Stereo Matching with StereoDiT and Transition Flow Matching Defom-stereo: Depth foundation model based stereo matching,

Reference 8

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Observation b14eb2b4-d4cc-4c61-80f3-6080e36aa660 · outbound

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

STEREOFLOW: Progressive Stereo Matching with StereoDiT and Transition Flow Matching A large dataset to train convolutional networks for disparity, optical flow, and scene flow estimation,

Reference 9

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Observation d5e66451-142a-445f-99f0-4d2bfcde2f9c · outbound

This paper cites On the synergies between machine learning and binocular stereo for depth estimation from images: A survey,.

STEREOFLOW: Progressive Stereo Matching with StereoDiT and Transition Flow Matching On the synergies between machine learning and binocular stereo for depth estimation from images: A survey,

Reference 10

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Observation 6d61ed02-a3bf-45c3-8fe4-ea829f7ea48f · outbound

This paper cites A Survey on Deep Stereo Matching in the Twenties.

STEREOFLOW: Progressive Stereo Matching with StereoDiT and Transition Flow Matching A Survey on Deep Stereo Matching in the Twenties

Reference 11

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Observation 6fda93b7-cd06-4954-8f7a-656e9fe7230f · outbound

This paper cites Pyramid stereo matching network,.

STEREOFLOW: Progressive Stereo Matching with StereoDiT and Transition Flow Matching Pyramid stereo matching network,

Reference 12

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Observation 343a1ca1-c17b-4944-be29-b4e0c8db60e7 · outbound

This paper cites On the over-smoothing problem of CNN based disparity estimation,.

STEREOFLOW: Progressive Stereo Matching with StereoDiT and Transition Flow Matching On the over-smoothing problem of CNN based disparity estimation,

Reference 13

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Observation c69379e8-bb85-4b24-a922-4e2845f7c0d0 · outbound

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

STEREOFLOW: Progressive Stereo Matching with StereoDiT and Transition Flow Matching Adaptive multi-modal cross-entropy loss for stereo matching,

Reference 14

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Observation 30137685-fddd-435f-9f92-9370e7392b20 · outbound

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

STEREOFLOW: Progressive Stereo Matching with StereoDiT and Transition Flow Matching Raft-stereo: Multilevel recurrent field transforms for stereo matching,

Reference 15

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Observation 636d1f1b-0421-4398-b9b8-cb017d313d1d · outbound

This paper cites Parallax attention for unsupervised stereo correspondence learning,.

STEREOFLOW: Progressive Stereo Matching with StereoDiT and Transition Flow Matching Parallax attention for unsupervised stereo correspondence learning,

Reference 16

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Observation 079fa269-4442-4972-9b7e-752410509376 · outbound

This paper cites Deep stereo using adaptive thin volume representation with uncertainty awareness,.

STEREOFLOW: Progressive Stereo Matching with StereoDiT and Transition Flow Matching Deep stereo using adaptive thin volume representation with uncertainty awareness,

Reference 17

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Observation f5f65c06-4e56-4ae2-999f-62c2584e4840 · outbound

This paper cites Uncertainty estimation for stereo matching based on evidential deep learning,.

STEREOFLOW: Progressive Stereo Matching with StereoDiT and Transition Flow Matching Uncertainty estimation for stereo matching based on evidential deep learning,

Reference 18

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Observation 0a96e22b-6e10-40b9-ae8a-264a4a5efa8b · outbound

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

STEREOFLOW: Progressive Stereo Matching with StereoDiT and Transition Flow Matching Elfnet: Evidential local- global fusion for stereo matching,

Reference 19

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Observation 3df318e8-1fbf-41e7-bc66-8d5b85c9376e · outbound

This paper cites Latentsplat: Autoencoding variational gaussians for fast generalizable 3d reconstruction,.

STEREOFLOW: Progressive Stereo Matching with StereoDiT and Transition Flow Matching Latentsplat: Autoencoding variational gaussians for fast generalizable 3d reconstruction,

Reference 20

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Observation 00a5543e-5153-4df9-90e5-fbf21c1bf46a · outbound

This paper cites Diffusion model for dense matching,.

STEREOFLOW: Progressive Stereo Matching with StereoDiT and Transition Flow Matching Diffusion model for dense matching,

Reference 21

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Observation 988074bf-a2f1-4014-960c-c3e91e304cee · outbound

This paper cites Diffsplat: Repurposing image diffusion models for scalable gaussian splat generation,.

STEREOFLOW: Progressive Stereo Matching with StereoDiT and Transition Flow Matching Diffsplat: Repurposing image diffusion models for scalable gaussian splat generation,

Reference 22

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Observation 36b6f0a4-186c-4195-a818-f643495d8100 · outbound

This paper cites DDT: Decoupled Diffusion Transformer.

STEREOFLOW: Progressive Stereo Matching with StereoDiT and Transition Flow Matching DDT: Decoupled Diffusion Transformer

Reference 23

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Observation 96089f0d-46aa-450a-83ba-09316de598ed · outbound

This paper cites DeCo: Frequency-Decoupled Pixel Diffusion for End-to-End Image Generation.

STEREOFLOW: Progressive Stereo Matching with StereoDiT and Transition Flow Matching DeCo: Frequency-Decoupled Pixel Diffusion for End-to-End Image Generation

Reference 24

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Observation 1bfe0103-ee07-460f-aa2a-0db6c550cfb9 · outbound

This paper cites Image super-resolution via iterative refinement,.

STEREOFLOW: Progressive Stereo Matching with StereoDiT and Transition Flow Matching Image super-resolution via iterative refinement,

Reference 25

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Observation 516afc09-5269-4896-a086-c588c0ac4f96 · outbound

This paper cites Resshift: Efficient diffusion model for image super-resolution by residual shifting,.

STEREOFLOW: Progressive Stereo Matching with StereoDiT and Transition Flow Matching Resshift: Efficient diffusion model for image super-resolution by residual shifting,

Reference 26

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This paper cites Group-wise correlation stereo network,.

STEREOFLOW: Progressive Stereo Matching with StereoDiT and Transition Flow Matching Group-wise correlation stereo network,

Reference 27

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Observation acea685c-0e70-4d59-9575-b2afdc9440cb · outbound

This paper cites IGEV++: Iterative Multi-range Geometry Encoding Volumes for Stereo Matching.

STEREOFLOW: Progressive Stereo Matching with StereoDiT and Transition Flow Matching IGEV++: Iterative Multi-range Geometry Encoding Volumes for Stereo Matching

Reference 28

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Observation bc3fddc0-a6bc-414e-983c-48b948506c19 · outbound

This paper cites RAFT: recurrent all-pairs field transforms for optical flow,.

STEREOFLOW: Progressive Stereo Matching with StereoDiT and Transition Flow Matching RAFT: recurrent all-pairs field transforms for optical flow,

Reference 29

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Observation 36854ec2-a702-4faa-a094-d7390adfbd51 · outbound

This paper cites High- frequency stereo matching network,.

STEREOFLOW: Progressive Stereo Matching with StereoDiT and Transition Flow Matching High- frequency stereo matching network,

Reference 30

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Observation 9e4c90ad-45ea-4e08-a99a-8db00bba69b8 · outbound

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

STEREOFLOW: Progressive Stereo Matching with StereoDiT and Transition Flow Matching Mocha-stereo: Motif channel attention network for stereo matching,

Reference 31

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Observation d126456e-d4fd-4fa2-831d-f247521a8137 · outbound

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

STEREOFLOW: Progressive Stereo Matching with StereoDiT and Transition Flow Matching Selective-stereo: Adaptive frequency information selection for stereo matching,

Reference 32

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Observation 2714013c-08e3-462d-8256-b269a3cee074 · outbound

This paper cites Depth anything V2,.

STEREOFLOW: Progressive Stereo Matching with StereoDiT and Transition Flow Matching Depth anything V2,

Reference 33

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Observation 9be74f07-0ad2-4491-9437-8d8fea3a5d86 · outbound

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

STEREOFLOW: Progressive Stereo Matching with StereoDiT and Transition Flow Matching End-to-end learning of geometry and context for deep stereo regression,

Reference 34

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This paper cites Pcw-net: Pyramid combination and warping cost volume for stereo matching,.

STEREOFLOW: Progressive Stereo Matching with StereoDiT and Transition Flow Matching Pcw-net: Pyramid combination and warping cost volume for stereo matching,

Reference 35

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This paper cites Attention concatenation volume for accurate and efficient stereo matching,.

STEREOFLOW: Progressive Stereo Matching with StereoDiT and Transition Flow Matching Attention concatenation volume for accurate and efficient stereo matching,

Reference 36

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Observation 7e6906e0-56af-45c4-9aeb-bb77d3c2e057 · outbound

This paper cites Mobilestereonet: Towards lightweight deep networks for stereo matching,.

STEREOFLOW: Progressive Stereo Matching with StereoDiT and Transition Flow Matching Mobilestereonet: Towards lightweight deep networks for stereo matching,

Reference 37

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This paper cites Lightstereo: Channel boost is all you need for efficient 2d cost aggregation,.

STEREOFLOW: Progressive Stereo Matching with StereoDiT and Transition Flow Matching Lightstereo: Channel boost is all you need for efficient 2d cost aggregation,

Reference 38

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Observation 76c5d7b6-0a4f-4a22-a810-b35a82ee944d · outbound

This paper cites Domain-invariant stereo matching networks,.

STEREOFLOW: Progressive Stereo Matching with StereoDiT and Transition Flow Matching Domain-invariant stereo matching networks,

Reference 39

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This paper cites S2m2: Scalable stereo matching model for reliable depth estimation,.

STEREOFLOW: Progressive Stereo Matching with StereoDiT and Transition Flow Matching S2m2: Scalable stereo matching model for reliable depth estimation,

Reference 40

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Observation 967663df-97f6-41a0-8294-610dfdb927a5 · outbound

This paper cites Diving into the Fusion of Monocular Priors for Generalized Stereo Matching.

STEREOFLOW: Progressive Stereo Matching with StereoDiT and Transition Flow Matching Diving into the Fusion of Monocular Priors for Generalized Stereo Matching

Reference 41

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Observation 561cf75a-013e-4eac-8460-898907988cf9 · outbound

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

STEREOFLOW: Progressive Stereo Matching with StereoDiT and Transition Flow Matching Revisiting stereo depth estimation from a sequence- to-sequence perspective with transformers,

Reference 42

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STEREOFLOW: Progressive Stereo Matching with StereoDiT and Transition Flow Matching Context-enhanced stereo transformer,

Reference 43

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This paper cites Unifying flow, stereo and depth estimation,.

STEREOFLOW: Progressive Stereo Matching with StereoDiT and Transition Flow Matching Unifying flow, stereo and depth estimation,

Reference 44

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Observation 34c0cc15-2141-4461-ac1a-0219eaddc2d1 · outbound

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

STEREOFLOW: Progressive Stereo Matching with StereoDiT and Transition Flow Matching Global occlusion-aware transformer for robust stereo matching,

Reference 45

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Observation 57b73782-26c6-45cb-b1d9-9cfcbcf820d4 · outbound

This paper cites Cascade cost volume for high-resolution multi-view stereo and stereo matching,.

STEREOFLOW: Progressive Stereo Matching with StereoDiT and Transition Flow Matching Cascade cost volume for high-resolution multi-view stereo and stereo matching,

Reference 46

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

STEREOFLOW: Progressive Stereo Matching with StereoDiT and Transition Flow Matching Cfnet: Cascade and fused cost volume for robust stereo matching,

Reference 47

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Observation 12b2438b-36c0-4e6c-b432-9c7c78f3c2e5 · outbound

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

STEREOFLOW: Progressive Stereo Matching with StereoDiT and Transition Flow Matching Practical stereo matching via cascaded recurrent network with adaptive correlation,

Reference 48

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This paper cites Uncertainty guided adaptive warping for robust and efficient stereo matching,.

STEREOFLOW: Progressive Stereo Matching with StereoDiT and Transition Flow Matching Uncertainty guided adaptive warping for robust and efficient stereo matching,

Reference 49

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Observation 4e8abb83-9d83-4166-ba08-84536cda652a · outbound

This paper cites Learning to adapt for stereo,.

STEREOFLOW: Progressive Stereo Matching with StereoDiT and Transition Flow Matching Learning to adapt for stereo,

Reference 50

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Observation d525ed78-02bd-4d96-ab21-3cdaf4f484e2 · outbound

This paper cites Matching-space stereo networks for cross-domain generalization,.

STEREOFLOW: Progressive Stereo Matching with StereoDiT and Transition Flow Matching Matching-space stereo networks for cross-domain generalization,

Reference 51

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Observation 79b526c1-f5d0-457a-8966-b663d5825ae1 · outbound

This paper cites Edgestereo: An effective multi-task learning network for stereo matching and edge detection,.

STEREOFLOW: Progressive Stereo Matching with StereoDiT and Transition Flow Matching Edgestereo: An effective multi-task learning network for stereo matching and edge detection,

Reference 52

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Observation 1210028a-c751-415a-a96c-661b58fba996 · outbound

This paper cites Segstereo: Exploiting semantic information for disparity estimation,.

STEREOFLOW: Progressive Stereo Matching with StereoDiT and Transition Flow Matching Segstereo: Exploiting semantic information for disparity estimation,

Reference 53

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Observation 3f173d5c-6890-46b9-b029-c2bbff14eeab · outbound

This paper cites Croco: Self- supervised pre-training for 3d vision tasks by cross-view completion,.

STEREOFLOW: Progressive Stereo Matching with StereoDiT and Transition Flow Matching Croco: Self- supervised pre-training for 3d vision tasks by cross-view completion,

Reference 54

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Observation fd41d0fd-0a22-474e-9fc3-d78be5da969c · outbound

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

STEREOFLOW: Progressive Stereo Matching with StereoDiT and Transition Flow Matching Robust synthetic-to-real transfer for stereo matching,

Reference 55

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Observation cde58848-696b-4bad-8ea9-e350af982940 · outbound

This paper cites Revisiting domain generalized stereo matching networks from a feature consistency perspective,.

STEREOFLOW: Progressive Stereo Matching with StereoDiT and Transition Flow Matching Revisiting domain generalized stereo matching networks from a feature consistency perspective,

Reference 56

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Observation 1220e8cd-bc8e-4484-9805-0f6ca4a2cefb · outbound

This paper cites Learning representa- tions from foundation models for domain generalized stereo matching,.

STEREOFLOW: Progressive Stereo Matching with StereoDiT and Transition Flow Matching Learning representa- tions from foundation models for domain generalized stereo matching,

Reference 57

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Observation c55a8d21-791e-475a-b720-e83e442633b7 · outbound

This paper cites Foundationstereo: Zero-shot stereo matching,.

STEREOFLOW: Progressive Stereo Matching with StereoDiT and Transition Flow Matching Foundationstereo: Zero-shot stereo matching,

Reference 58

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This paper cites Stereo anywhere: Robust zero-shot deep stereo matching even where either stereo or mono fail,.

STEREOFLOW: Progressive Stereo Matching with StereoDiT and Transition Flow Matching Stereo anywhere: Robust zero-shot deep stereo matching even where either stereo or mono fail,

Reference 59

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Observation 118367a5-32a3-494e-9e86-f4f41473d89a · outbound

This paper cites Monster: Marry monodepth to stereo unleashes power,.

STEREOFLOW: Progressive Stereo Matching with StereoDiT and Transition Flow Matching Monster: Marry monodepth to stereo unleashes power,

Reference 60

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Observation ec333798-3ec4-48c7-bc61-1845f70e7550 · outbound

This paper cites BridgeDepth: Bridging Monocular and Stereo Reasoning with Latent Alignment.

STEREOFLOW: Progressive Stereo Matching with StereoDiT and Transition Flow Matching BridgeDepth: Bridging Monocular and Stereo Reasoning with Latent Alignment

Reference 61

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Observation 3826dd56-d3ca-402c-9469-bb80859398de · outbound

This paper cites Score-based generative modeling through stochastic differential equations,.

STEREOFLOW: Progressive Stereo Matching with StereoDiT and Transition Flow Matching Score-based generative modeling through stochastic differential equations,

Reference 62

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Observation b80c3c82-cbe3-4f06-ae3f-7f5386f3ff13 · outbound

This paper cites Flow matching for generative modeling,.

STEREOFLOW: Progressive Stereo Matching with StereoDiT and Transition Flow Matching Flow matching for generative modeling,

Reference 63

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Observation 0cdcdd54-ad90-426e-bcdc-15f86426fc1e · outbound

This paper cites Stochastic Interpolants: A Unifying Framework for Flows and Diffusions.

STEREOFLOW: Progressive Stereo Matching with StereoDiT and Transition Flow Matching Stochastic Interpolants: A Unifying Framework for Flows and Diffusions

Reference 64

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Observation 14aa1eb0-9995-4270-b8bb-5f145302da95 · outbound

This paper cites Depthfm: Fast generative monocular depth estimation with flow matching,.

STEREOFLOW: Progressive Stereo Matching with StereoDiT and Transition Flow Matching Depthfm: Fast generative monocular depth estimation with flow matching,

Reference 65

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Observation e19f5748-1a47-4844-ac1f-657f51f9260a · outbound

This paper cites Lotus: Diffusion-based visual foundation model for high- quality dense prediction,.

STEREOFLOW: Progressive Stereo Matching with StereoDiT and Transition Flow Matching Lotus: Diffusion-based visual foundation model for high- quality dense prediction,

Reference 66

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Observation a3cf2803-1abf-4f87-8baa-335703f7fa11 · outbound

This paper cites Pixel- perfect depth with semantics-prompted diffusion transformers,.

STEREOFLOW: Progressive Stereo Matching with StereoDiT and Transition Flow Matching Pixel- perfect depth with semantics-prompted diffusion transformers,

Reference 67

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Observation 9edafe75-90eb-4299-ae39-041d67b03062 · outbound

This paper cites MVDD: multi-view depth diffusion mod- els,.

STEREOFLOW: Progressive Stereo Matching with StereoDiT and Transition Flow Matching MVDD: multi-view depth diffusion mod- els,

Reference 68

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Observation 546d6187-8a98-48c5-8293-5ba578eee6b1 · outbound

This paper cites Single-stage diffusion nerf: A unified approach to 3d generation and reconstruction,.

STEREOFLOW: Progressive Stereo Matching with StereoDiT and Transition Flow Matching Single-stage diffusion nerf: A unified approach to 3d generation and reconstruction,

Reference 69

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Observation ae8d3c2f-1ceb-46a9-8f35-5eee69362bce · outbound

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STEREOFLOW: Progressive Stereo Matching with StereoDiT and Transition Flow Matching Deterministic point cloud diffusion for denoising,

Reference 70

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Observation 1f1d9a4f-05ef-40f4-81da-0c092a64cb98 · outbound

This paper cites Exploiting diffusion prior for real-world image super-resolution,.

STEREOFLOW: Progressive Stereo Matching with StereoDiT and Transition Flow Matching Exploiting diffusion prior for real-world image super-resolution,

Reference 71

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Observation 7e44178c-c70e-4a65-9a07-031d39007379 · outbound

This paper cites Residual denoising diffusion models,.

STEREOFLOW: Progressive Stereo Matching with StereoDiT and Transition Flow Matching Residual denoising diffusion models,

Reference 72

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Observation 4778757f-4847-45de-b93d-0a5bc8298641 · outbound

This paper cites Diffcap: Diffusion-based real-time human motion capture using sparse imus and a monocular camera,.

STEREOFLOW: Progressive Stereo Matching with StereoDiT and Transition Flow Matching Diffcap: Diffusion-based real-time human motion capture using sparse imus and a monocular camera,

Reference 73

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Observation cedd9db6-d47c-44b1-94f7-15d34b1abb42 · outbound

This paper cites Coshmdm: Contact and shape-aware latent motion diffusion model for human in- teraction generation,.

STEREOFLOW: Progressive Stereo Matching with StereoDiT and Transition Flow Matching Coshmdm: Contact and shape-aware latent motion diffusion model for human in- teraction generation,

Reference 74

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Observation d42c156b-98a8-4d31-859d-71697d7318e2 · outbound

This paper cites Coreeditor: Correspondence- constrained diffusion for consistent 3d editing,.

STEREOFLOW: Progressive Stereo Matching with StereoDiT and Transition Flow Matching Coreeditor: Correspondence- constrained diffusion for consistent 3d editing,

Reference 75

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Observation 69deb63d-9e44-440e-ac6c-bd308e5a1d19 · outbound

This paper cites Diffuvolume: Diffusion model for volume based stereo matching,.

STEREOFLOW: Progressive Stereo Matching with StereoDiT and Transition Flow Matching Diffuvolume: Diffusion model for volume based stereo matching,

Reference 76

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This paper cites D3roma: Disparity diffusion-based depth sens- ing for material-agnostic robotic manipulation,.

STEREOFLOW: Progressive Stereo Matching with StereoDiT and Transition Flow Matching D3roma: Disparity diffusion-based depth sens- ing for material-agnostic robotic manipulation,

Reference 77

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Observation ce351a26-9da0-40a8-9f1d-ff3100a10118 · outbound

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STEREOFLOW: Progressive Stereo Matching with StereoDiT and Transition Flow Matching Flowdiffuser: Advancing optical flow estimation with diffusion models,

Reference 78

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Observation c3318e77-bafd-4180-8791-e7587047f258 · outbound

This paper cites Lightweight and accurate multi-view stereo with confidence-aware diffusion model,.

STEREOFLOW: Progressive Stereo Matching with StereoDiT and Transition Flow Matching Lightweight and accurate multi-view stereo with confidence-aware diffusion model,

Reference 79

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This paper cites Rethinking iterative stereo matching from a diffusion bridge model perspective,.

STEREOFLOW: Progressive Stereo Matching with StereoDiT and Transition Flow Matching Rethinking iterative stereo matching from a diffusion bridge model perspective,

Reference 80

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Observation a6abb7af-e320-4193-9472-bc73bee642e0 · outbound

This paper cites High- resolution image synthesis with latent diffusion models,.

STEREOFLOW: Progressive Stereo Matching with StereoDiT and Transition Flow Matching High- resolution image synthesis with latent diffusion models,

Reference 81

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Observation eae12ba5-73ad-44c2-bd3c-b522ad421fe4 · outbound

This paper cites Scaling rectified flow transformers for high-resolution image synthesis,.

STEREOFLOW: Progressive Stereo Matching with StereoDiT and Transition Flow Matching Scaling rectified flow transformers for high-resolution image synthesis,

Reference 82

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Observation ff7247b8-2bf0-44de-8511-f493af2c9b1b · outbound

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STEREOFLOW: Progressive Stereo Matching with StereoDiT and Transition Flow Matching FLUX.1 Kontext: Flow Matching for In-Context Image Generation and Editing in Latent Space

Reference 83

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Observation 60d99136-6957-48e2-bad9-df3a225133aa · outbound

This paper cites Back to Basics: Let Denoising Generative Models Denoise.

STEREOFLOW: Progressive Stereo Matching with StereoDiT and Transition Flow Matching Back to Basics: Let Denoising Generative Models Denoise

Reference 84

Resolution: unresolved; no resolver link, observed 2026-08-01T11:10:14.253473Z

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Observation a55ce2ce-6ebc-4142-8cc2-5980d9b2f2e8 · outbound

This paper cites PixelFlow: Pixel-Space Generative Models with Flow.

STEREOFLOW: Progressive Stereo Matching with StereoDiT and Transition Flow Matching PixelFlow: Pixel-Space Generative Models with Flow

Reference 85

Resolution: unresolved; no resolver link, observed 2026-08-01T11:10:14.258534Z

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Observation 688ea2d2-b462-4c62-8806-bec70df73d7d · outbound

This paper cites Pyramidal flow matching for efficient video generative modeling,.

STEREOFLOW: Progressive Stereo Matching with StereoDiT and Transition Flow Matching Pyramidal flow matching for efficient video generative modeling,

Reference 86

Resolution: unresolved; no resolver link, observed 2026-08-01T11:10:14.263323Z

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Observation 21c98685-d98d-4f94-b287-2d241eda1ad6 · outbound

This paper cites Denoising diffusion probabilistic mod- els,.

STEREOFLOW: Progressive Stereo Matching with StereoDiT and Transition Flow Matching Denoising diffusion probabilistic mod- els,

Reference 87

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This paper cites Generative modeling by estimating gradients of the data distribution,.

STEREOFLOW: Progressive Stereo Matching with StereoDiT and Transition Flow Matching Generative modeling by estimating gradients of the data distribution,

Reference 88

Resolution: unresolved; no resolver link, observed 2026-08-01T11:10:14.275387Z

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Observation c8d345c8-d008-4ed9-b44c-d0988c2de590 · outbound

This paper cites Elucidating the design space of diffusion-based generative models,.

STEREOFLOW: Progressive Stereo Matching with StereoDiT and Transition Flow Matching Elucidating the design space of diffusion-based generative models,

Reference 89

Resolution: unresolved; no resolver link, observed 2026-08-01T11:10:14.281624Z

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Observation 059b2310-faf6-4e59-97e2-ecf18ec14856 · outbound

This paper cites Analyzing and improving the training dynamics of diffusion models,.

STEREOFLOW: Progressive Stereo Matching with StereoDiT and Transition Flow Matching Analyzing and improving the training dynamics of diffusion models,

Reference 90

Resolution: unresolved; no resolver link, observed 2026-08-01T11:10:14.287527Z

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Observation 34f9f11d-1955-4fd4-ac8a-b3bd85932166 · outbound

This paper cites Denoising diffusion implicit mod- els,.

STEREOFLOW: Progressive Stereo Matching with StereoDiT and Transition Flow Matching Denoising diffusion implicit mod- els,

Reference 91

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Observation e9214d69-e750-4c47-84d9-045f71d9bc22 · outbound

This paper cites Fast sampling of diffusion models with exponential integrator,.

STEREOFLOW: Progressive Stereo Matching with StereoDiT and Transition Flow Matching Fast sampling of diffusion models with exponential integrator,

Reference 92

Resolution: unresolved; no resolver link, observed 2026-08-01T11:10:14.300765Z

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Observation 844b17a8-ece9-46bd-9e3d-94d3aecdc2f5 · outbound

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STEREOFLOW: Progressive Stereo Matching with StereoDiT and Transition Flow Matching Improved denoising diffusion prob- abilistic models,

Reference 93

Resolution: unresolved; no resolver link, observed 2026-08-01T11:10:14.307140Z

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Observation 94256687-78e5-4743-998d-8d467a0ed576 · outbound

This paper cites On the Importance of Noise Scheduling for Diffusion Models.

STEREOFLOW: Progressive Stereo Matching with StereoDiT and Transition Flow Matching On the Importance of Noise Scheduling for Diffusion Models

Reference 94

Resolution: unresolved; no resolver link, observed 2026-08-01T11:10:14.313140Z

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Observation 4d4d6d64-99ca-4c6f-94e8-93e4d1fbbba2 · outbound

This paper cites Flow straight and fast: Learning to gen- erate and transfer data with rectified flow,.

STEREOFLOW: Progressive Stereo Matching with StereoDiT and Transition Flow Matching Flow straight and fast: Learning to gen- erate and transfer data with rectified flow,

Reference 95

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Observation 5e3f21e8-ef88-4cba-826b-630a615cc553 · outbound

This paper cites Flowing from words to pixels: A noise-free framework for cross-modality evolution,.

STEREOFLOW: Progressive Stereo Matching with StereoDiT and Transition Flow Matching Flowing from words to pixels: A noise-free framework for cross-modality evolution,

Reference 96

Resolution: unresolved; no resolver link, observed 2026-08-01T11:10:14.324277Z

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Observation ed4d6c4b-bc97-436e-8699-a78cab45c809 · outbound

This paper cites Flowtok: Flowing seamlessly across text and image tokens,.

STEREOFLOW: Progressive Stereo Matching with StereoDiT and Transition Flow Matching Flowtok: Flowing seamlessly across text and image tokens,

Reference 97

Resolution: unresolved; no resolver link, observed 2026-08-01T11:10:14.328579Z

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Observation 545f3f01-abe4-4adf-b607-f345bff68fad · outbound

This paper cites Multisample flow matching: Straightening flows with minibatch couplings,.

STEREOFLOW: Progressive Stereo Matching with StereoDiT and Transition Flow Matching Multisample flow matching: Straightening flows with minibatch couplings,

Reference 98

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Observation 575f83d0-6909-4d63-b09f-7a0df0cdc77c · outbound

This paper cites Improving and generalizing flow- based generative models with minibatch optimal transport,.

STEREOFLOW: Progressive Stereo Matching with StereoDiT and Transition Flow Matching Improving and generalizing flow- based generative models with minibatch optimal transport,

Reference 99

Resolution: unresolved; no resolver link, observed 2026-08-01T11:10:14.339404Z

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Observation 28fcd592-08d9-44df-a57b-206d23d8d5c7 · outbound

This paper cites Stochastic interpolants with data-dependent cou- plings,.

STEREOFLOW: Progressive Stereo Matching with StereoDiT and Transition Flow Matching Stochastic interpolants with data-dependent cou- plings,

Reference 100

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