ORena SAVE FOCUS Challenge — PROCEDURE Track

Foreign Object Contextual Understanding in Surgery


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Long-context surgical VQA for foreign object understanding

This is the PROCEDURE Track of the ORena SAVE FOCUS Challenge. The track evaluates whether vision-language models can answer clinically relevant questions from long laparoscopic video contexts up to full procedures, focusing on long-horizon memory, persistent foreign object tracking, aggregation over time, and retrieval-status reasoning.

The broader ORena SAVE FOCUS Challenge benchmarks vision-language models on clinically grounded visual question answering for foreign object understanding in minimally invasive surgery. The goal is to advance AI methods that can support intraoperative quality assurance and patient safety.

The PROCEDURE Track is the most demanding track of the challenge. It tests whether models can reason over extended surgical video contexts where safety-relevant information may depend on events that occurred much earlier in the operation.

Start here

Register for the challenge

Join the central forum

Download the first data batch

Use the orena-focus package


Why this challenge matters

Clinical relevance

In minimally invasive surgery, foreign objects such as sponges, needles, clips, drains, specimen bags, and similar objects may be introduced into the abdominal cavity during a procedure. Retained foreign objects after major operations are rare but clinically relevant adverse events associated with patient harm [Badiee et al., 2025].

Technical challenge

Foreign object understanding over full procedures requires models to maintain consistent representations of objects across long videos. Long-video benchmarks have shown the importance of evaluating models beyond short clips by requiring reasoning over extended visual context [Wu et al., 2024].


Benchmark at a glance

Task type
Long-context surgical video question answering
Input
long surgical video (up to full procedure) + meta data (type of procedure) + question
Output
short text answer
Focus
Long-context foreign object understanding
PROCEDURE time budget
30 seconds per question
PROCEDURE hardware
80GB VRAM GPU
Prize pool
$50k+ across tracks
Submission
Docker container

The three ORena SAVE FOCUS tracks

FRAME
Track

Single-image understanding

Answer clinically relevant questions from one laparoscopic image. This track evaluates visual perception, foreign object identification, counting, attributes, and spatial localization.

SEGMENT
Track

Short-video understanding

Answer questions from short video segments of up to 5 minutes. This track evaluates local temporal reasoning, short-term tracking, and action understanding.

PROCEDURE
Track

Long-context understanding

Answer questions over long video contexts up to full procedures. This track evaluates long-horizon memory, persistent object tracking, aggregation over time, and retrieval-status reasoning.

You are here.


PROCEDURE Track

The PROCEDURE Track evaluates a model’s ability to answer clinically relevant questions from long laparoscopic video contexts up to full procedures. The task targets long-context surgical video understanding skills such as:

  • persistent foreign object tracking across extended surgical video
  • long-horizon memory for objects inserted, manipulated, occluded, or retrieved earlier in the procedure
  • aggregation of foreign object counts and events over time
  • retrieval-status reasoning for objects that must be accounted for before the end of the operation
  • complex reasoning across multiple objects, time points, and surgical events

The input consists of a long procedure video context, the procedure name as meta data and a question. The submitted algorithm must return a text answer. All methods must be fully automated.

Algorithm input

Whole procedure video, meta data (type of procedure, timestamp) + question

Exact input format will follow the official submission template repository.

Algorithm output

Short text answer

Exact answer formatting and validation details will follow the official submission template repository.


Data and scientific background

The first released data batch, HeiCo-FOCUS, is based on Heidelberg colorectal surgery videos and provides clinically grounded VQA pairs for foreign object understanding. The dataset covers five capability categories: object recognition and identity matching, temporal grounding, aggregation, event and procedural understanding, and complex reasoning.

The PROCEDURE Track builds on prior work in surgical visual question answering, where models answer clinically relevant questions from surgical scenes [Seenivasan et al., 2022].

The PROCEDURE Track also connects to the broader development of long-video understanding benchmarks, which evaluate whether multimodal models can reason beyond isolated frames and short static contexts [Fu et al., 2025].

For the PROCEDURE Track, the focus is on the long-context part of this benchmark. This provides a demanding setting for evaluating whether models can maintain object identity, aggregate evidence, and answer safety-relevant questions over extended surgical video contexts.

First data batch
HeiCo-FOCUS VQA
Number of videos
30
Expert involvement
Clinical and technical experts
Motivation
Foreign object safety and long-context understanding


Figure 1: Overview of the HeiCo-FOCUS benchmark, showing a) the clinical motivation and b) providing an overview of the first batch dataset.


Submission and evaluation

  • Submissions must be made through the challenge website.
  • Algorithms are submitted as Docker containers.
  • Containers must run without internet access.
  • Inference is limited to a single GPU.
  • The PROCEDURE Track time budget is 30 seconds per question on an 80GB VRAM GPU.
  • The PROCEDURE Track includes a technical leaderboard and a clinical leaderboard.
  • During pre-evaluation, each team may submit up to 10 times, subject to possible adjustment depending on compute constraints.
  • For the PROCEDURE Track, teams must beat both baselines on at least one of the leaderboards, technical or clinical, to proceed to the final test stage.
  • Teams must submit a method description with sufficient technical detail for interpretation of the results.

Prizes and recognition

$50k+ prize pool

A prize pool of at least $50k has been secured across the ORena SAVE FOCUS Challenge tracks. The PROCEDURE Track is planned to receive approximately 40% of the total prize money, split approximately equally between the Technical and Clinical leaderboards.

Publication opportunity

Teams that beat the baselines may be invited as co-authors on the planned challenge publication, subject to the official rules and submission requirements.


Resources

Registration Register for the ORena SAVE FOCUS Challenge
Central forum ORena SAVE FOCUS Forum
First data batch HeiCo-FOCUS VQA on Hugging Face
Python package orena-focus GitHub repository
Submission template Will be released soon.

Webinar recording

The ORena SAVE FOCUS webinar recording is available here after May 28th: