Update README.md

README.md

@@ -31,23 +31,26 @@ size_categories:
 
 ## 📃 Overview
 
-> This repo contains the official evaluation code and dataset for the paper
-> **"EPIC-Bench: A Perception-Centric Benchmark for Fine-Grained Embodied Visual Grounding in Vision-Language Models"**
 
-**EPIC-Bench** is a **Mask-Grounding-based** benchmark designed to evaluate a VLM’s **Visual Perception** capability in **Embodied Scenarios**.
-
-<p align="center">
-  <img src="https://epic-bench.github.io/EPIC-Bench/img/20260302-192636.png" alt="EPIC-Bench teaser" width="100%"/>
-</p>
-
-📚 EPIC-Bench covers **3 High-Level Categories** and **23 Task Types**, following the realistic **Embodied Workflow**:
+📚 **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.
@@ -61,7 +64,6 @@ The goal is to measure whether models can reliably perceive the critical **Visua
 
 ## 📋 Todo
 
-
 - [x] Evaluation code for EPIC-Bench
 - [x] The EPIC-Bench datasets
 - [ ] Make the evaluation pipeline compatible with mask outputs
@@ -88,7 +90,7 @@ Please refer to the [EPIC-Bench Homepage](https://epic-bench.github.io/EPIC-Benc
 
 ## 📜 License
 
-Please add an explicit `LICENSE` file before open-sourcing. If EPIC-Bench annotations or images have redistribution constraints, publish them separately (e.g., Hugging Face / ModelScope) and keep this repo code-only + small examples.
+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