README.md

# H2VU-Benchmark: A Comprehensive Benchmark for Hierarchical Holistic Video Understanding



## 👀 H²VU-Benchmark Overview


H²VU-Benchmark is designed to comprehensively assess the capabilities of video understanding models, particularly in real-world scenarios. It addresses limitations of existing benchmarks by focusing on **extended video durations, advanced task complexity, and diversified real-world data.**

## Key Features

*   **Three-Tier Hierarchical Competency Classification:** (L-1 to L-3) with **10,183 evaluation tasks** covering a broad spectrum of diverse data.
*   **Two Main Categories:**
    *   **Offline General Video:** Employs common perception and reasoning tasks, along with novel tasks focusing on **countercommonsense comprehension** and **trajectory tracking.** (27 evaluation task types)
    *   **Online Streaming Video:** Utilizes standard perception and reasoning tasks. (20 evaluation task types)

## Key Differentiators from Existing Benchmarks

Our work distinguishes itself through three key features:

*   **Extended Video Duration:**
    *   Encompasses a diverse range from a **few seconds to 1.5 hours**, significantly expanding the temporal scope.
    *   Evaluates models' ability to capture **short-term dynamics** and model **long-term dependencies.**
*   **Advanced Task Complexity:**
    *   Builds on traditional perceptual and reasoning tasks with the introduction of two new modules:
        *   **Counterfactual Reasoning:** Assesses vision-oriented understanding through tasks that defy common sense (e.g., implausible causal relationships).
        *   **Trajectory State Tracking:** Evaluates the ability to track and predict the states and trajectories of targets in complex dynamic scenes.
*   **Diversified Real-World Data:**
    *   Incorporates **first-person streaming video data** to better simulate real-world streaming data processing needs.
    *   Explores multimodal models' performance in understanding first-person streaming video, crucial for AI agents functioning as real-world assistants or autonomous agents.