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README.md
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<div align="center">
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<h1>Context as Memory: Scene-Consistent Interactive Long Video Generation with Memory Retrieval</h1>
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<h1>SIGGRAPH Asia 2025</h1>
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<p>
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<a href="https://context-as-memory.github.io/">[Project page]</a>
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<a href="https://arxiv.org/pdf/2506.03141">[ArXiv]</a>
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<a href="https://huggingface.co/datasets/KwaiVGI/Context-as-Memory-Dataset">[Dataset]</a>
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</p>
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</div>
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# File Structure
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To prepare the dataset for use, merge the parts into a single zip file using the following command:
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```bash
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cat Context-as-Memory-Dataset_* > Context-as-Memory-Dataset.zip
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```
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After extracting `Context-as-Memory-Dataset.zip`, the dataset will be organized as follows:
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```
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Context-as-Memory-Dataset
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├── frames
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│ ├── AncientTempleEnv_0
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│ │ ├── 0000.png
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│ │ ├── 0001.png
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│ │ ├── 0002.png
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│ │ └── ...
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│ ├── AncientTempleEnv_1
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│ │ ├── 0000.png
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│ │ ├── 0001.png
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│ │ ├── 0002.png
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│ │ └── ...
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│ └── ...
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│
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├── jsons
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│ ├── AncientTempleEnv_0.json
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│ ├── AncientTempleEnv_1.json
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│ └── ...
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│
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├── overlap_labels
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│ ├── AncientTempleEnv_0
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│ │ ├── 0.json
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│ │ ├── 1.json
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│ │ ├── 2.json
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│ │ └── ...
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│ ├── AncientTempleEnv_1
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│ │ ├── 0.json
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│ │ ├── 1.json
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│ │ ├── 2.json
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│ │ └── ...
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│ └── ...
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│
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└── captions.txt
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```
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# Explanation of Dataset Parts
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- **`frames/`**: 100 subdirectories, each containing 7,601 video frame images.
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- **`jsons/`**: 100 JSON files, each storing the camera pose (position + rotation) of every frame in the corresponding long video.
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- **`overlap_labels/`**: 100 subdirectories, each containing 7,601 JSON files, where each file records the indices of overlapping frames corresponding to that frame.
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- **`captions.txt`**: Captions annotated for a segment of a long video, from a given starting frame to an ending frame.
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- We also provide a simple code file, `tools.py`, which can convert (x, y, z, yaw, pitch) into RT, and can also select a specific frame as the reference frame to align the RT of other frames to its coordinate system.
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