| --- |
| language: |
| - en |
| license: other |
| license_name: memact-component-licenses |
| license_link: LICENSE.md |
| task_categories: |
| - visual-question-answering |
| tags: |
| - spatial-reasoning |
| - streaming |
| - memory |
| - active-exploration |
| pretty_name: MemAct / StreaMemAct |
| --- |
| |
| # MemAct / StreaMemAct |
|
|
| [Paper](https://vfishc.github.io/memact/assets/memact-paper.pdf) · [Project](https://vfishc.github.io/memact/) · [Code](https://github.com/vfishc/memact) |
|
|
| Yuxi Wei, Wei Huang, Qirui Chen, Lu Hou, Xiaojuan Qi. |
|
|
| This repository hosts the prepared StreaMemAct data suite accompanying **MemAct: Streaming Spatial Understanding with Memory and Active Exploration**. The repository identifier is `vfishc/memact`. The repository is public; data upload is in progress. |
|
|
| ## Contents |
|
|
| | Component | Count / scope | Directory | |
| | --- | --- | --- | |
| | Current QA | 302,661 answer turns | data/train/current_memory | |
| | Memory QA | 402,662 answer turns | data/train/current_memory | |
| | Memory supervision | 519,948 writes; 556,635 retrieval calls, additional to QA counts | Within Current/Memory streams | |
| | Action SFT | 294,677 items; 534,752 camera transitions | data/train/action | |
| | RL | 14,001 tasks and branch observations | data/rl | |
| | Main evaluation | 20,000 turns, including graphs for 1,245 Action questions | data/evaluation | |
| | Timing | 2,000 separate questions | data/evaluation | |
| | Simulation media and GLBs | Rendered videos and associated scene assets | media/simulation | |
| | Rendering dependencies | Scene inputs, textures/HDRIs and configurations | assets/rl | |
| | Frozen Action render inputs | 1,245 question configurations | generation/frozen_action | |
| | Metadata | Frames, timestamps, camera/object records and evidence references | metadata/episodes | |
| | Reconstruction | Upstream download/reconstruction mappings | reconstruction | |
| |
| The prepared manifest records 206 archives totaling 589,652,365,064 bytes, plus supporting metadata. Archives retain relative media references and checksums. See release_manifest.json, release_statistics.json and RELEASE_GUIDE.txt after upload for extraction and verification. |
|
|
| ## Usage and provenance |
|
|
| Use the code repository's generation, reconstruction, training and evaluation entry points. Retrieve original ScanNet, ScanNet++ and ARKitScenes recordings from their providers; this release supplies reconstruction mappings rather than redistributing original recordings. A video does not replace its frame/time mapping. Evaluator-only answers and geometry must not be included in model inputs. Weights are not included. |
|
|
| The prepared training selection contains 1M QA turns; memory writes and retrieval calls are counted separately. It replaces selected recording-ID overlap with the frozen evaluation bank. Strict physical-space disjointness is not claimed because distinct real recordings can share a physical space. Release counts are separate from paper-era intermediate composition. |
|
|
| Technical validation covers annotation/media references, branch coverage, reconstruction samples and runtime tests. It is not a rerun of the paper's benchmark scores. The supplied native inference backend does not reproduce the persistent cross-call compact KV cache or paper latency. |
|
|
| ## Licenses |
|
|
| See [LICENSE.md](LICENSE.md). Original MemAct annotation contributions use CC BY 4.0, and original code uses Apache-2.0. Upstream assets and derived content retain their source terms. The mixed repository is not licensed wholesale under CC BY 4.0; applicable asset-specific source terms remain controlling. |
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|
