MemCam: Memory-Augmented Camera Control for Consistent Video Generation
Paper β’ 2603.26193 β’ Published
IJCNN 2026 | Paper | Project Page | GitHub
MemCam is a memory-augmented framework for scene-consistent interactive video generation, built on Wan2.1-T2V-1.3B. It treats previously generated frames as external memory and dynamically retrieves the most viewpoint-relevant frames via co-visibility estimation, enabling faithful scene reconstruction even after 360Β° camera rotations.
| File | Description |
|---|---|
dit_step20000.ckpt |
MemCam DiT checkpoint (trained 20k steps) |
git clone https://github.com/newhorizon2005/MemCam.git
cd MemCam
# Download this model
huggingface-cli download newhorizon2005/MemCam dit_step20000.ckpt --local-dir models/MemCam
# Run inference
python inference_memcam.py
@inproceedings{gao2026memcam,
title = {MemCam: Memory-Augmented Camera Control for Consistent Video Generation},
author = {Gao, Xinhang and Guan, Junlin and Luo, Shuhan and Li, Wenzhuo and Tan, Guanghuan and Wang, Jiacheng},
booktitle = {International Joint Conference on Neural Networks (IJCNN)},
year = {2026}
}
Base model
Wan-AI/Wan2.1-T2V-1.3B