Update README.md

README.md

@@ -1,3 +1,106 @@
----
-license: cc-by-4.0
----
+---
+license: cc-by-4.0
+---
+# MotionHalluc Benchmark
+
+This repository contains the **MotionHalluc benchmark**, a dataset designed for evaluating motion hallucination and motion reasoning in video-based multimodal models.
+
+---
+
+## 📌 Overview
+
+MotionHalluc introduces three evaluation tasks that require models to compare, reason about, and verify human motion patterns across videos. The benchmark is constructed using curated annotations and motion representations derived from human motion estimation pipelines.
+
+We provide:
+- Structured QA annotations for motion reasoning
+- Motion representations extracted using a state-of-the-art motion reconstruction model
+- Evaluation-ready dataset splits
+
+---
+
+## 📁 Dataset Structure
+
+### 1. `anno/`
+Contains all annotation files, including:
+- Three MotionHalluc tasks (QA-based evaluation)
+- Original curated annotations used to construct the benchmark
+
+Each file is in JSON format.
+
+### 2. `motion_4dHumans/`
+Contains motion representations corresponding to each video sample.
+
+- Format: `.npy`
+- Extracted using a pretrained 4D human motion reconstruction pipeline
+- Each file corresponds to a video ID used in the QA annotations
+
+---
+
+## 🎥 Video Data
+
+We distribute **annotations and motion representations only**.
+
+Since we do not own the original videos, users are required to download them separately.
+
+- Fit3D dataset: https://fit3d.imar.ro/
+
+The videos are used solely as input references for motion extraction and evaluation alignment.
+
+---
+
+## ⚙️ Motion Extraction
+
+Motion representations are obtained using a pretrained 4D human motion reconstruction method:
+
+:contentReference[oaicite:1]{index=1}
+
+This approach is used to extract 3D human motion trajectories from video inputs.
+
+---
+
+## 💻 Preprocessing & Evaluation Code
+
+We provide video processing and evaluation scripts in the official code repository:
+
+👉 GitHub repository: https://your-github-link-here
+
+This includes:
+- Video preprocessing pipeline.
+- Evaluation scripts for all three MotionHalluc tasks.
+- Accuracy calculation script.
+
+---
+
+## 🔄 Fit3D Ground Truth Motion Processing
+
+Due to dataset licensing restrictions, we do **not redistribute Fit3D-derived motion data**.
+
+However:
+- We will release the full Fit3D ground-truth motion processing pipeline upon acceptance.
+- This includes conversion from raw motion capture format to our benchmark representation.
+
+In the current submission, all experiments are conducted using the **4D-Humans-based motion representation**, which already demonstrates strong performance and serves as a reliable proxy for kinematic evaluation.
+
+---
+
+## 📊 Benchmark Usage
+
+Each sample in MotionHalluc contains:
+- A question about motion comparison or reasoning
+- Multiple-choice or binary answers
+- Corresponding motion representation for each video
+
+Example format:
+```json
+{
+  "0001": {
+        "v1": "Bench/s03/band_pull_apart/band_pull_apart_front_215_304.mp4",
+        "v2": "Bench/s04/band_pull_apart/band_pull_apart_front_236_345.mp4",
+        "q": "You are given a query motion in Video1 and a reference motion in Video2. Which of the following correction accurate and necessary to improve the query motion in Video1 based on the reference motion in Video2?",
+        "c": [
+            "Hands level with your head at the beginning",
+            "At the beginning, keep your hands below head level"
+        ],
+        "a": "A"
+    },
+}