Recent planning

[zengbohan0217]

For OpenDCAI-MMgen team developers:

1. Check the VLA, 3D, reasoning code; (keep doing this)
2. Keep refining the test code files, add interaction guidance;
3. accomplish the benchmark evaluation code. (this one is hard maybe we will finish this later).

[zengbohan0217]

Keep check the codebase:
WorldCam(recorded): https://github.com/cvlab-kaist/WorldCam
Infinite-world(recorded): https://github.com/MeiGen-AI/Infinite-World
WorldGrow(recorded): https://github.com/world-grow/WorldGrow
inspatio-world(recorded): https://github.com/inspatio/inspatio-world
mosaicmem(recorded)：https://mosaicmem.github.io/mosaicmem/
pointworld(recorded): https://github.com/NVlabs/PointWorld
DROID-W(recorded): https://github.com/MoyangLi00/DROID-W
pi-0.6(recorded): https://huggingface.co/exla-ai/openpie-0.6
gigaworld-policy(recorded): https://github.com/GigaAI-research/GigaWorld-Policy
vggt-world(recorded): https://arxiv.org/pdf/2603.12655
LeWorldModel(recorded): https://github.com/lucas-maes/le-wm , training framework
omniworldbench(recorded): https://arxiv.org/pdf/2603.22212 , benchmark
WildWorld(recorded): https://github.com/ShandaAI/WildWorld
Matrix-Game-3(recorded): https://github.com/SkyworkAI/Matrix-Game/tree/main/Matrix-Game-3
interactive video generation(recorded): https://github.com/KlingAIResearch/ShotStream
omniforcing: https://github.com/OmniForcing/OmniForcing
Sekai(recorded): https://arxiv.org/pdf/2506.15675 training dataset
worldlab marble-1.1(recorded): https://radiancefields.com/world-labs-releases-marble-1.1-and-marble-1.1-plus
LIBERO-Para: https://huggingface.co/papers/2603.28301
every-embodied: https://github.com/datawhalechina/every-embodied , excellent learning framework for vla
fastwam: https://github.com/yuantianyuan01/FastWAM important for evaluation
Hunyuan-embodied: https://github.com/Tencent-Hunyuan/HY-Embodied
DreamX-World: https://github.com/AMAP-ML/DreamX-World
CFC: https://frank-zy-dou.github.io/projects/CFC/
beingbeyond: https://github.com/BeingBeyond/Being-H
wildDet3D: https://github.com/allenai/WildDet3D well exhibition, important work
HappyOyster: https://www.happyoyster.cn
Hunyuan: https://github.com/Tencent-Hunyuan/HY-World-2.0

[zengbohan0217]

advanced survey:
Learning to Model the World: A Survey of World Models in Artificial Intelligence(recorded) : https://www.preprints.org/frontend/manuscript/5086594a01b6a0b251820cb03ea9a8f6/download_pub

[zengbohan0217]

Important Team:

1. unitreerobotics: https://huggingface.co/unitreerobotics
2. beingbeyond(智在无界)：https://research.beingbeyond.com/being-h07