Surgical phase recognition

Description from the archive archive 2025-07-28.

Benchmarks archive 2025-07-28

4 leaderboard tables shown for this task, 4 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

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

Subtasks archive 2025-07-28

2 subtasks in the archive's task tree.

Most implemented papers archive 2025-07-28

30 shown of 31 papers with code (69 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.

• Pixel-Wise Recognition for Holistic Surgical Scene Understanding
  20 Jan 2024 3 repositories listed Syntology ran 7 of 13 samples · 6 unverified · 1 pointer-only (licence)
  To exploit our proposed benchmark, we introduce the Transformers for Actions, Phases, Steps, and Instrument Segmentation (TAPIS) model, a general architecture that combines a global video feature extractor with…
• HecVL: Hierarchical Video-Language Pretraining for Zero-shot Surgical Phase Recognition
  16 May 2024 2 repositories listed
  By disentangling embedding spaces of different hierarchical levels, the learned multi-modal representations encode short-term and long-term surgical concepts in the same model.
• Not End-to-End: Explore Multi-Stage Architecture for Online Surgical Phase Recognition
  10 Jul 2021 2 repositories listed
  To address the problem, we propose a new non end-to-end training strategy and explore different designs of multi-stage architecture for surgical phase recognition task.
• TeCNO: Surgical Phase Recognition with Multi-Stage Temporal Convolutional Networks
  24 Mar 2020 2 repositories listed
  Automatic surgical phase recognition is a challenging and crucial task with the potential to improve patient safety and become an integral part of intra-operative decision-support systems.
• Surg-3M: A Dataset and Foundation Model for Perception in Surgical Settings
  25 Mar 2025 1 repository listed
  Our experimental results show that SurgFM outperforms state-of-the-art models in multiple downstream tasks, including significant gains in surgical phase recognition (+8.
• EndoMamba: An Efficient Foundation Model for Endoscopic Videos via Hierarchical Pre-training
  26 Feb 2025 1 repository listed
  First, to mitigate computational inefficiencies, we propose the EndoMamba backbone, optimized for real-time inference.
• Dual Invariance Self-training for Reliable Semi-supervised Surgical Phase Recognition
  29 Jan 2025 1 repository listed
  Accurate surgical phase recognition is crucial for advancing computer-assisted interventions, yet the scarcity of labeled data hinders training reliable deep learning models.
• SurgPLAN++: Universal Surgical Phase Localization Network for Online and Offline Inference
  19 Sep 2024 1 repository listed
  To ensure a global understanding of the surgical procedure, we devise a phase localization strategy for SurgPLAN++ to predict phase segments across the entire video through phase proposals.
• SPRMamba: Surgical Phase Recognition for Endoscopic Submucosal Dissection with Mamba
  18 Sep 2024 1 repository listed
  Endoscopic Submucosal Dissection (ESD) is a minimally invasive procedure initially developed for early gastric cancer treatment and has expanded to address diverse gastrointestinal lesions.
• DACAT: Dual-stream Adaptive Clip-aware Time Modeling for Robust Online Surgical Phase Recognition
  10 Sep 2024 1 repository listed
  In the other stream, DACAT fine-tunes a new frame encoder to extract the frame-wise feature at the current moment.
• Surgformer: Surgical Transformer with Hierarchical Temporal Attention for Surgical Phase Recognition
  7 Aug 2024 1 repository listed
  Moreover, we propose a novel Hierarchical Temporal Attention (HTA) to capture both global and local information within varied temporal resolutions from a target frame-centric perspective.
• MuST: Multi-Scale Transformers for Surgical Phase Recognition
  24 Jul 2024 1 repository listed
  Phase recognition in surgical videos is crucial for enhancing computer-aided surgical systems as it enables automated understanding of sequential procedural stages.
• SR-Mamba: Effective Surgical Phase Recognition with State Space Model
  11 Jul 2024 1 repository listed
  Inspired by the recent success of Mamba, a state space model with linear scalability in sequence length, this paper presents SR-Mamba, a novel attention-free model specifically tailored to meet the challenges of…
• EgoSurgery-Phase: A Dataset of Surgical Phase Recognition from Egocentric Open Surgery Videos
  30 May 2024 1 repository listed
  To address this issue, we introduce a new egocentric open surgery video dataset for phase recognition, named EgoSurgery-Phase.
• Encoding Surgical Videos as Latent Spatiotemporal Graphs for Object and Anatomy-Driven Reasoning
  11 Dec 2023 1 repository listed
  Recently, spatiotemporal graphs have emerged as a concise and elegant manner of representing video clips in an object-centric fashion, and have shown to be useful for downstream tasks such as action recognition.
• Self-Supervised Learning for Endoscopic Video Analysis
  23 Aug 2023 1 repository listed
  To fully exploit the power of SSL, we create sizable unlabeled endoscopic video datasets for training MSNs.
• TUNeS: A Temporal U-Net with Self-Attention for Video-based Surgical Phase Recognition
  19 Jul 2023 1 repository listed
  In addition, we propose to train the feature extractor, a standard CNN, together with an LSTM on preferably long video segments, i.
• Metrics Matter in Surgical Phase Recognition
  23 May 2023 1 repository listed
  Surgical phase recognition is a basic component for different context-aware applications in computer- and robot-assisted surgery.
• LoViT: Long Video Transformer for Surgical Phase Recognition
  15 May 2023 1 repository listed
  Our results demonstrate the effectiveness of our approach in achieving state-of-the-art performance of surgical phase recognition on two datasets of different surgical procedures and temporal sequencing characteristics…
• Whether and When does Endoscopy Domain Pretraining Make Sense?
  30 Mar 2023 1 repository listed
  In this work, we investigate the need for endoscopy domain-specific pretraining based on downstream objectives.
• SKiT: a Fast Key Information Video Transformer for Online Surgical Phase Recognition
  1 Jan 2023 1 repository listed
  We highlight that the inference time of SKiT is constant, and independent from the input length, making it a stable choice for keeping a record of important global information, that appears on long surgical videos,…
• Towards Holistic Surgical Scene Understanding
  8 Dec 2022 1 repository listed
  Second, we present Transformers for Action, Phase, Instrument, and steps Recognition (TAPIR) as a strong baseline for surgical scene understanding.
• Dissecting Self-Supervised Learning Methods for Surgical Computer Vision
  1 Jul 2022 1 repository listed
  Correct transfer of these methods to surgery, as described and conducted in this work, leads to substantial performance gains over generic uses of SSL - up to 7.
• Free Lunch for Surgical Video Understanding by Distilling Self-Supervisions
  19 May 2022 1 repository listed
  Our key insight is to distill knowledge from publicly available models trained on large generic datasets4 to facilitate the self-supervised learning of surgical videos.
• Less is More: Surgical Phase Recognition from Timestamp Supervision
  16 Feb 2022 1 repository listed
  Our study uncovers unique insights of surgical phase recognition with timestamp supervisions: 1) timestamp annotation can reduce 74% annotation time compared with the full annotation, and surgeons tend to annotate those…
• Exploring Segment-level Semantics for Online Phase Recognition from Surgical Videos
  22 Nov 2021 1 repository listed
  Automatic surgical phase recognition plays a vital role in robot-assisted surgeries.
• LensID: A CNN-RNN-Based Framework Towards Lens Irregularity Detection in Cataract Surgery Videos
  2 Jul 2021 1 repository listed
  In particular, we propose (I) an end-to-end recurrent neural network to recognize the lens-implantation phase and (II) a novel semantic segmentation network to segment the lens and pupil after the implantation phase.
• Trans-SVNet: Accurate Phase Recognition from Surgical Videos via Hybrid Embedding Aggregation Transformer
  17 Mar 2021 1 repository listed
  In this paper, we introduce, for the first time in surgical workflow analysis, Transformer to reconsider the ignored complementary effects of spatial and temporal features for accurate surgical phase recognition.
• Multi-Task Recurrent Convolutional Network with Correlation Loss for Surgical Video Analysis
  13 Jul 2019 1 repository listed Syntology ran 2 of 2 samples · 0 unverified · 2 pointer-only (licence)
  Mutually leveraging both low-level feature sharing and high-level prediction correlating, our MTRCNet-CL method can encourage the interactions between the two tasks to a large extent, and hence can bring about benefits…
• Learning from a tiny dataset of manual annotations: a teacher/student approach for surgical phase recognition
  30 Nov 2018 1 repository listed
  Vision algorithms capable of interpreting scenes from a real-time video stream are necessary for computer-assisted surgery systems to achieve context-aware behavior.

Syntology lines on 2 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.