Dense Pixel Correspondence Estimation

Benchmarks archive 2025-07-28

5 leaderboard tables shown for this task, 5 with rows (a “benchmark” on this site is a table with at least one row, as on /sota), ordered by row count. “Best model” is the first row in the archive's own order at snapshot; nothing is re-ranked here and metric direction is not recorded in the archive. PwC's Trend sparklines are not in the archive, so that column is omitted.

Syntology column: samples harvested from the paper's repositories and executed on synthesized fixtures; “ran” is not a correctness claim and does not order the table. A dash means no Syntology record for that paper, not a recorded non-run. Read from the graph 2026-09-24.

Libraries

Not in the archive: the export carries no per-task library table, so there is nothing to show at snapshot 2025-07-28.

Datasets archive 2025-07-28

4 datasets whose archive record lists this task, ordered by the archive's paper count.

Subtasks archive 2025-07-28

No subtask under this task in the archive's task tree.

Most implemented papers archive 2025-07-28

16 shown of 16 papers with code (17 tagged with this task in all), ordered by repositories listed in the archive, not by stars (the archive holds no stars, so PwC's “Social” and “Latest” sorts cannot be reproduced). Papers without a page here are shown as plain text.

• PWC-Net: CNNs for Optical Flow Using Pyramid, Warping, and Cost Volume
  7 Sep 2017 21 repositories listed Syntology ran 3 of 3 samples · 0 unverified · 3 pointer-only (licence)
  It then uses the warped features and features of the first image to construct a cost volume, which is processed by a CNN to estimate the optical flow.
• FlowNet 2.0: Evolution of Optical Flow Estimation with Deep Networks
  6 Dec 2016 12 repositories listed Syntology ran 2 of 21 samples · 19 unverified · 3 pointer-only (licence)
  Particularly on small displacements and real-world data, FlowNet cannot compete with variational methods.
• Optical Flow Estimation using a Spatial Pyramid Network
  3 Nov 2016 8 repositories listed
  We learn to compute optical flow by combining a classical spatial-pyramid formulation with deep learning.
• Learning Accurate Dense Correspondences and When to Trust Them
  5 Jan 2021 4 repositories listed Syntology ran 1 of 1 samples · 0 unverified
  Establishing dense correspondences between a pair of images is an important and general problem.
• DGC-Net: Dense Geometric Correspondence Network
  19 Oct 2018 4 repositories listed
  This paper addresses the challenge of dense pixel correspondence estimation between two images.
• GOCor: Bringing Globally Optimized Correspondence Volumes into Your Neural Network
  16 Sep 2020 2 repositories listed Syntology ran 18 of 22 samples · 4 unverified · 22 pointer-only (licence)
  We propose GOCor, a fully differentiable dense matching module, acting as a direct replacement to the feature correlation layer.
• GLU-Net: Global-Local Universal Network for Dense Flow and Correspondences
  11 Dec 2019 2 repositories listed Syntology ran 1 of 1 samples · 0 unverified · 1 pointer-only (licence)
  Establishing dense correspondences between a pair of images is an important and general problem, covering geometric matching, optical flow and semantic correspondences.
• A Tale of Two Features: Stable Diffusion Complements DINO for Zero-Shot Semantic Correspondence
  24 May 2023 1 repository listed
  Text-to-image diffusion models have made significant advances in generating and editing high-quality images.
• GPS-GLASS: Learning Nighttime Semantic Segmentation Using Daytime Video and GPS data
  27 Jul 2022 1 repository listed
  Nighttime semantic segmentation is especially challenging due to a lack of annotated nighttime images and a large domain gap from daytime images with sufficient annotation.
• GAN-Supervised Dense Visual Alignment
  9 Dec 2021 1 repository listed Syntology ran 2 of 2 samples · 0 unverified
  We propose GAN-Supervised Learning, a framework for learning discriminative models and their GAN-generated training data jointly end-to-end.
• Deep Matching Prior: Test-Time Optimization for Dense Correspondence
  6 Jun 2021 1 repository listed
  Conventional techniques to establish dense correspondences across visually or semantically similar images focused on designing a task-specific matching prior, which is difficult to model.
• Warp Consistency for Unsupervised Learning of Dense Correspondences
  7 Apr 2021 1 repository listed Syntology ran 2 of 3 samples · 1 unverified · 3 pointer-only (licence)
  From our observations and empirical results, we design a general unsupervised objective employing two of the derived constraints.
• COTR: Correspondence Transformer for Matching Across Images
  25 Mar 2021 1 repository listed Syntology ran 1 of 2 samples · 1 unverified
  We propose a novel framework for finding correspondences in images based on a deep neural network that, given two images and a query point in one of them, finds its correspondence in the other.
• Space-Time Correspondence as a Contrastive Random Walk
  25 Jun 2020 1 repository listed Syntology ran 4 of 14 samples · 10 unverified
  We cast correspondence as prediction of links in a space-time graph constructed from video.
• Joint Recovery of Dense Correspondence and Cosegmentation in Two Images
  1 Jun 2016 1 repository listed
  We propose a new technique to jointly recover cosegmentation and dense per-pixel correspondence in two images.
• DeepMatching: Hierarchical Deformable Dense Matching
  25 Jun 2015 1 repository listed
  We introduce a novel matching algorithm, called DeepMatching, to compute dense correspondences between images.

Syntology lines on 9 of the papers shown; no Syntology record for the others (a paper without an arXiv id cannot be joined to the graph, and absence from the graph layer is not a recorded non-run). “Ran” means the sample executed on a synthesized fixture, not that the paper's result was reproduced. Read from the graph 2026-09-24.