| --- |
| license: apache-2.0 |
| pretty_name: EPIC-Bench |
| task_categories: |
| - visual-question-answering |
| - object-detection |
| language: |
| - en |
| Modalities: |
| - Image |
| - Text |
| tags: |
| - embodied-perception |
| - mask-grounding |
| - vision-language-models |
| size_categories: |
| - 1K<n<10K |
| configs: |
| - config_name: default |
| data_files: |
| - split: train |
| path: metadata.jsonl |
| --- |
| |
|
|
| <div align="center"> |
| |
| # 🎯 EPIC-Bench: A Perception-Centric Benchmark for Fine-Grained Embodied Visual Grounding in Vision-Language Models |
|
|
| [](https://epic-bench.github.io/EPIC-Bench/) |
| [](https://epic-bench.github.io/EPIC-Bench/) |
| [](https://huggingface.co/datasets/rxc205/EPIC-Bench) |
| [](https://github.com/rxc205/EPIC-Bench-Eval#-epic-bench-evaluation-toolkit) |
| [](https://github.com/rxc205/EPIC-Bench-Eval/blob/main/LICENSE) |
| </div> |
|
|
| ## 📃 Overview |
|
|
|
|
| 📚 **EPIC-Bench** is a **Mask-Grounding-based** benchmark designed to evaluate a VLM’s **Visual Perception** capability in **Embodied Scenarios**. EPIC-Bench covers **3 High-Level Categories** and **23 Task Types**, following the realistic **Embodied Workflow**: |
|
|
| - 🎯 **TargetLocalization**: **Pinpoint** the right object in the scene from a natural-language instruction. |
| - 🧭 **Navigation**: **Approach** the target step by step by reading key visual cues along the way. |
| - 🤲 **Manipulation**: **Operate** on the target through fine-grained, action-oriented **Grounded Perception**. |
|
|
| <p align="center"> |
| <img src="https://epic-bench.github.io/EPIC-Bench/img/20260302-192636.png" alt="EPIC-Bench teaser" width="100%"/> |
| </p> |
|
|
| The goal is to measure whether models can reliably perceive the critical **Visual** information required throughout the **Embodied Process**. |
|
|
| <p align="center"> |
| <img src="https://raw.githubusercontent.com/rxc205/EPIC-Bench-Eval/refs/heads/main/images/bmk_cases.png" alt="EPIC-Bench bmk_cases" width="100%"/> |
| </p> |
| <p align="center"> |
| <em>Example visualization of EPIC-Bench. For more, visit our <a href="https://epic-bench.github.io/EPIC-Bench/">Project Page</a> or <a href="https://huggingface.co/datasets/rxc205/EPIC-Bench">download the dataset</a> to explore the full benchmark locally.</em> |
| </p> |
|
|
| ## ✨ Highlights |
|
|
| - **Embodied-Scenario** evaluation of VLM **Visual Perception** capability. |
| - Focus on **Visual Grounding / Perception** without language shortcut exploitation. |
| - **Diverse** and **Fine-Grained** task design. |
|
|
| ## 📰 News |
|
|
| - [2026.5.15] 🚀 [HuggingFace](https://huggingface.co/datasets/rxc205/EPIC-Bench) and [ModelScope](https://www.modelscope.cn/datasets/macarich/EPIC-Bench) Dataset are available! |
| - [2026.5.15] 🚀 [Project Page](https://epic-bench.github.io/EPIC-Bench/) and [Evaluation Code](https://github.com/rxc205/EPIC-Bench-Eval) are released, the arXiv paper will come soon. |
|
|
| ## 📋 Todo |
|
|
| - [x] Evaluation code for EPIC-Bench |
| - [x] The EPIC-Bench datasets |
| - [ ] Make the evaluation pipeline compatible with mask outputs |
|
|
|
|
| ## 🏆 Leaderboard and Benchmark |
|
|
| Please refer to the [EPIC-Bench Homepage](https://epic-bench.github.io/EPIC-Bench/) for: |
|
|
| - Leaderboard |
| - Full dataset downloads |
| - EPIC-Bench data examples |
|
|
| ## 📚 Citation |
|
|
| ```BibTeX |
| @article{EPIC-Bench, |
| title={EPIC-Bench: A Perception-Centric Benchmark for Fine-Grained Embodied Visual Grounding in Vision-Language Models}, |
| author={XXX, XXX, XXX}, |
| journal={}, |
| year={2026} |
| } |
| ``` |
|
|
| ## 📜 License |
|
|
|
|
| This project is licensed under the Apache License 2.0 - see the [LICENSE](https://github.com/rxc205/EPIC-Bench-Eval/blob/main/LICENSE) file for details. |
|
|
| ## 🙏 Acknowledgements |
|
|
| - **ms-swift** for open-source VLM inference: [ms-swift](https://swift.readthedocs.io/zh-cn/latest/) |
| - **lmms-eval** for API/closed-source evaluation: [lmms-eval](https://github.com/EvolvingLMMs-Lab/lmms-eval) |
