README.md

---
language:
  - en
pretty_name: Code2Video-Compass
license: cc-by-nc-4.0
tags:
  - benchmark
  - video-generation
  - code-generation
  - multimodal
task_categories:
  - text-to-video
configs:
  - config_name: t2v
    data_files:
      - split: train
        path: preview/t2v/*.parquet
  - config_name: i2v
    data_files:
      - split: train
        path: preview/i2v/*.parquet
  - config_name: v2v
    data_files:
      - split: train
        path: preview/v2v/*.parquet
---

<p align="center">
  <img src="assets/code2video-compass.svg" width="140" alt="Code2Video-Compass logo">
</p>

<h1 align="center">Code2Video-Compass: A Comprehensive Benchmark for General-Purpose Code-Based Video Generation across T2V, I2V, and V2V</h1>

<p align="center">Zhenghan Chen, Zekai Shao, Xin Lin, Leting Cheng, and Siming Chen</p>

<p align="center" style="margin:0;line-height:24px">
  <a href="https://code2video-compass.github.io/"><img style="display:inline-block;margin:0;vertical-align:middle" src="https://img.shields.io/badge/Homepage-Code2Video--Compass-16837c.svg?style=flat-square" alt="Homepage: Code2Video-Compass"></a>
  <a href="https://arxiv.org/abs/2610.28416"><img style="display:inline-block;margin:0;vertical-align:middle" src="https://img.shields.io/badge/arXiv-2610.28416-b31b1b.svg?style=flat-square" alt="arXiv paper"></a>
  <a href="https://github.com/code2video-compass/Code2Video-Compass"><img style="display:inline-block;margin:0;vertical-align:middle" src="https://img.shields.io/badge/GitHub-Code2Video--Compass-24292e.svg?logo=github&amp;style=flat-square" alt="GitHub: Code2Video-Compass"></a>
  <br>
  <img style="display:inline-block;margin:0;vertical-align:middle" src="assets/license-badges.svg" width="366" alt="Code license: Apache-2.0; Data license: CC BY-NC 4.0">
</p>

<h3 align="center">The official dataset repository of Code2Video-Compass</h3>

<p align="center">
  <a href="#1-overview">Overview</a> &nbsp;|&nbsp;
  <a href="#2-task-formats">Task formats</a> &nbsp;|&nbsp;
  <a href="#4-download-and-use">Download and use</a> &nbsp;|&nbsp;
  <a href="#6-evaluation">Evaluation</a> &nbsp;|&nbsp;
  <a href="#7-data-fields">Data fields</a>
</p>

**Preview release: 180 tasks — 60 T2V, 60 I2V, and 60 V2V.** The full benchmark contains 2,104 tasks and will be released in a future update.

## 1. Overview

<p align="center">
  <img src="assets/overview-20261022.jpg" width="100%" alt="Code2Video-Compass overview: three input settings, a general-purpose code stack, 15 models, 10 video categories, and dual-level evaluation">
</p>
<p align="center"><sub>The benchmark evaluates 15 multimodal large language models (MLLMs) on code-based text-to-video (T2V), image-to-video (I2V), and video-to-video (V2V) generation through a dual-level framework combining 12 objective metrics with five subjective metrics.</sub></p>

**Code2Video-Compass** evaluates whether multimodal models can translate detailed visual and temporal requirements into executable programs that render complete videos. It assesses instruction following, visual quality, temporal coherence, and reference fidelity across diverse creative tasks.

Code2Video-Compass benchmarks 15 multimodal large language models (MLLMs) on 2,104 code-based video generation tasks across text-to-video (T2V), image-to-video (I2V), and video-to-video (V2V) settings. The benchmark spans 10 creative categories and employs 12 objective and five subjective metrics.

The tasks are organized into two collections:

- **Source-paired tasks:** 573 curated source videos, each associated with three corresponding instructions and selected visual references.
- **Independent tasks:** 385 separately constructed tasks, comprising text instructions, image-conditioned tasks, and clip-conditioned tasks.

The full benchmark comprises:

| Collection | T2V | I2V | V2V | Total |
|---|---:|---:|---:|---:|
| Source-paired | 573 | 573 | 573 | 1719 |
| Independent | 145 | 120 | 120 | 385 |
| **Total** | **718** | **693** | **693** | **2,104** |

Each task includes its instruction, structured annotations, and an evaluation checklist.

## 2. Task Formats

| Setting | Model input | What the model needs to produce |
|---|---|---|
| **T2V — Text to Video** | A detailed text instruction | Code that renders the specified visual content and event progression |
| **I2V — Image to Video** | A text instruction and a reference keyframe | Code that incorporates the reference state at the instructed stage of a complete animation |
| **V2V — Video to Video** | A text instruction and a reference clip | Code that incorporates the clip's content and dynamics into the instructed full sequence |

I2V images specify a reference state to incorporate at the instructed stage. V2V clips provide
selected source intervals. The task instruction and reference summary specify their role in the output.

## 3. Data Construction and Coverage

The source-paired collection selects complete animations through keyword-based retrieval, screening, deduplication, quality assessment, and manual review. The independent collection constructs additional tasks from curated text, image, and video inputs.

<p align="center">
  <img src="assets/construction.jpg" width="100%" alt="Data construction pipeline with independent and paired task sets">
</p>
<p align="center"><sub>Data construction pipeline. (A) Independent tasks are developed from curated text seeds, images, and video clips. (B) Paired tasks share a complete source video across T2V, I2V, and V2V. (C) Both sets undergo prompt construction, QA checklist development, and annotation, yielding 2,104 tasks.</sub></p>

### Full benchmark distributions

<p align="center">
  <img src="assets/distributions.jpg" width="100%" alt="Distributions of video families, motion types, subject types, event counts, and durations">
</p>
<p align="center"><sub>Dataset distributions over 958 records: 573 source-paired groups and 385 independent tasks. Families, motion types, and subject types can have multiple labels.</sub></p>

<p align="center">
  <img src="assets/complexity.jpg" width="100%" alt="Family-by-complexity distributions and T2V, I2V, V2V prompt token lengths">
</p>
<p align="center"><sub>Category-wise construction, dynamic animation, and state-dependency complexity, and prompt lengths across input settings.</sub></p>

### Creative coverage

| Family | Scope |
|---|---|
| 1. Explainer Motion Graphics | Concepts, mechanisms, processes, and systems |
| 2. Branding & Promotional Motion | Brand identities, product promotion, and campaigns |
| 3. Kinetic Typography | Text-driven motion and editorial typography |
| 4. UI & Product Motion | Interface workflows, dashboards, and HUDs |
| 5. Data & Infographic Animation | Quantitative stories, relationships, timelines, and geographic information |
| 6. Title Sequences | Openings, titles, closings, and credits |
| 7. Broadcast & Show Graphics | News, sports, entertainment, and program packaging |
| 8. Illustrative & Character Narrative | Character stories and illustrated scene narratives |
| 9. Abstract & Experimental Motion | Procedural geometry, particles, and formal experiments |
| 10. 3D Motion | Objects, products, environments, and procedural or simulated 3D |

The 24-subtype taxonomy and definitions are available in [taxonomy.json](taxonomy.json).

### Complexity annotations

| Axis | Description | Labels |
|---|---|---|
| **C — Construction complexity** | Complexity of the visual structures and elements to be constructed | C1–C3 |
| **D — Dynamic Animation Complexity** | Complexity of changes, motion coordination, and temporal organization | D1–D3 |
| **S — State dependency span** | How long an established object or state constrains later stages | S1–S3 |

## 4. Download and Use

Each task setting is provided in Parquet, JSONL, and CSV formats with identical records.

### Read the local release

Run these commands from this release directory:

```bash
pip install datasets
```

```python
from datasets import load_dataset

t2v = load_dataset("parquet", data_files={"train": "preview/t2v/*.parquet"}, split="train")
i2v = load_dataset("parquet", data_files={"train": "preview/i2v/*.parquet"}, split="train")
v2v = load_dataset("parquet", data_files={"train": "preview/v2v/*.parquet"}, split="train")

print(t2v[0]["prompt"])
print(i2v[0]["reference_frame_summary"])
```

### Read from Hugging Face

The preview defines three configs: `t2v`, `i2v`, and `v2v`.
Load a setting directly from the dataset repository:

```python
dataset = load_dataset("code2video-compass/Code2Video-Compass", "i2v", split="train")
```

Each config provides its 60 preview tasks through the `train` split.

### Reference media

Task tables provide prompts and, for conditioned tasks, reference URLs and timestamps. Retrieve
the reference media from its listed source; documentation figures are in `assets/`. Timestamps
are relative to the original source video: I2V uses `keyframe_timestamp_s`, and V2V uses `keyclip_start_s` and
`keyclip_end_s`. Video timestamps apply to video-derived I2V references and V2V clips.

## 5. Pairing and File Organization

```text
README.md
assets/
preview/
  t2v/       # 60 tasks
  i2v/       # 60 tasks
  v2v/       # 60 tasks
pair_index.csv
reference_sources.json
taxonomy.json
schema.json
manifest.json
```

Join corresponding tasks by `sample_id`; `pair_index.csv` lists the tasks included in this preview.

## 6. Evaluation

The evaluation framework reports automatic measurements and model-assisted assessments:

| Part | What is evaluated |
|---|---|
| Execution and efficiency | Whether code produces a video, and output-token consumption |
| Automatic video measurements | Technical quality, aesthetic quality, motion smoothness, and local/global text–video alignment |
| Reference fidelity | Keyframe perceptual/structural fidelity for I2V; clip sequence, appearance, and motion fidelity for V2V |
| Instruction following | Checklist QA against the requirements of the corresponding task |
| Holistic quality | NC: content coherence and integrity; VD: visual design and graphic richness; MQ: motion quality and richness; VE: viewer engagement |

Model outputs and scores are published separately from the task tables.

## 7. Data Fields

The T2V, I2V, and V2V tables contain 14, 17, and 18 columns, respectively, with `qa` as the final column. Multi-valued annotations are stored as ordered lists of strings.

### Shared text fields

| Field | Description |
|---|---|
| `sample_id` | Group ID shared by corresponding source-paired tasks |
| `task_id` | Unique task ID, including its T2V/I2V/V2V suffix |
| `task` | Input setting: t2v, i2v, or v2v |
| `prompt` | Task-specific instruction provided to the model |
| `global_description` | Complete overall description of the video |
| `video_categories` | All video-family names, as a native list of complete strings |
| `subtypes` | All subtype names, as a native list of complete strings |
| `subjects` | Primary subject type labels as a native list, such as ["Graphic"] |
| `motion_types` | All motion types, as a native list |
| `events` | All visual event descriptions, as a native list in order |
| `construction_complexity` | C label (C1–C3) |
| `dynamic_complexity` | D label (D1–D3) |
| `dependency_span` | S label (S1–S3) |

### I2V reference fields

| Field | Description |
|---|---|
| `reference_url` | Source media URL or source dataset item locator |
| `reference_frame_summary` | Complete original description of the reference image |
| `keyframe_timestamp_s` | Recorded keyframe time in seconds for video-derived images; null for standalone images |

### V2V reference fields

| Field | Description |
|---|---|
| `reference_url` | Source media URL or source dataset item locator |
| `reference_clip_summary` | Complete original description of the reference clip |
| `keyclip_start_s`, `keyclip_end_s` | Recorded clip interval in seconds relative to the original source video used for this task |

### QA checklist — final column

`qa` contains the shared questions and the specific questions for this task only.
It is an ordered list of records with `section`, `dimension`, `name`, `question`, and
`expected_answer`.
T2V includes FullVideoSpecific, I2V includes KeyframeSpecific, and V2V includes
ReferenceClipSpecific, following the shared questions.

## 8. Release Notes

[manifest.json](manifest.json) records counts and data-file hashes;
[schema.json](schema.json) records the field types.

Reference media are linked through source URLs or dataset locators, subject to their availability and licensing terms.

## Citation

If you find Code2Video-Compass useful, please consider citing our paper:

```bibtex
@misc{chen2026code2videocompasscomprehensivebenchmarkgeneralpurpose,
      title={Code2Video-Compass: A Comprehensive Benchmark for General-Purpose Code-Based Video Generation across T2V, I2V, and V2V},
      author={Zhenghan Chen and Zekai Shao and Xin Lin and Leting Cheng and Siming Chen},
      year={2026},
      eprint={2610.28416},
      archivePrefix={arXiv},
      primaryClass={cs.CV},
      url={https://arxiv.org/abs/2610.28416}
}
```