SOTAVerified

Surgical phase recognition

The first 40 videos are used for training, the last 40 videos are used for testing.

Papers

Showing 125 of 69 papers

TitleStatusHype
Surg-3M: A Dataset and Foundation Model for Perception in Surgical SettingsCode2
HecVL: Hierarchical Video-Language Pretraining for Zero-shot Surgical Phase RecognitionCode2
Pixel-Wise Recognition for Holistic Surgical Scene UnderstandingCode2
EndoMamba: An Efficient Foundation Model for Endoscopic Videos via Hierarchical Pre-trainingCode1
Surgformer: Surgical Transformer with Hierarchical Temporal Attention for Surgical Phase RecognitionCode1
MuST: Multi-Scale Transformers for Surgical Phase RecognitionCode1
EgoSurgery-Phase: A Dataset of Surgical Phase Recognition from Egocentric Open Surgery VideosCode1
Encoding Surgical Videos as Latent Spatiotemporal Graphs for Object and Anatomy-Driven ReasoningCode1
Self-Supervised Learning for Endoscopic Video AnalysisCode1
LoViT: Long Video Transformer for Surgical Phase RecognitionCode1
Whether and When does Endoscopy Domain Pretraining Make Sense?Code1
Towards Holistic Surgical Scene UnderstandingCode1
Dissecting Self-Supervised Learning Methods for Surgical Computer VisionCode1
Free Lunch for Surgical Video Understanding by Distilling Self-SupervisionsCode1
Less is More: Surgical Phase Recognition from Timestamp SupervisionCode1
Exploring Segment-level Semantics for Online Phase Recognition from Surgical VideosCode1
Not End-to-End: Explore Multi-Stage Architecture for Online Surgical Phase RecognitionCode1
Trans-SVNet: Accurate Phase Recognition from Surgical Videos via Hybrid Embedding Aggregation TransformerCode1
TeCNO: Surgical Phase Recognition with Multi-Stage Temporal Convolutional NetworksCode1
Holistic Surgical Phase Recognition with Hierarchical Input Dependent State Space Models0
Recognizing Surgical Phases Anywhere: Few-Shot Test-time Adaptation and Task-graph Guided RefinementCode0
Meta-SurDiff: Classification Diffusion Model Optimized by Meta Learning is Reliable for Online Surgical Phase Recognition0
ReSW-VL: Representation Learning for Surgical Workflow Analysis Using Vision-Language Model0
Surgeons vs. Computer Vision: A comparative analysis on surgical phase recognition capabilities0
Federated EndoViT: Pretraining Vision Transformers via Federated Learning on Endoscopic Image Collections0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1SF-TMN(ASFormer)Acc95.43Unverified
2LoViTF190.24Unverified
3MSNF189.6Unverified
4MuSTF185.57Unverified
5MoCo V2 Surg SSL - TCN headF181.6Unverified
6TCNF180.3Unverified
#ModelMetricClaimedVerifiedStatus
1MuSTF177.25Unverified
2CAMMA1 (challenge model)F168.8Unverified
3HIKVision (challenge model)F165.4Unverified
4CUHK (challenge model)F165Unverified
5MoCo V2 Surg SSL - TCN headF164.7Unverified
#ModelMetricClaimedVerifiedStatus
1MuSTmAP98.08Unverified
2TAPISmAP97.14Unverified
3TAPIRmAP94.24Unverified
#ModelMetricClaimedVerifiedStatus
1MuSTmAP79.14Unverified
2TAPISmAP76.72Unverified