3.5M-param anime upscaler applies Looped-DiT recurrence, gains +0.6dB in 4 loops
NobodySnJake · reddit · 2026-10-08
Redditor gtboy1994 adapted Looped-DiT's weight-shared recurrent blocks into a direct RGB restoration model: Baikal LoopSR x2, an anime upscaler with only 3.5M unique parameters.
Architecture
- Bicubic residual; 2 pre-blocks + 4 shared middle blocks recurrently reused for 4 passes + 2 post-blocks; attention only in the shared stage; deep supervision on loop outputs; PixelShuffle for 2x reconstruction
- Not diffusion; an experiment proving recurrent shared blocks can do real super-resolution work
Results
- At the 24k checkpoint, Clean PSNR rises 41.885 → 42.480 and Degraded 39.610 → 40.162 across loops 1–4 (+0.55–0.60 dB total); each loop improves instead of collapsing
- Final SSIM 0.9841 (clean) / 0.9761 (degraded)
- Anime hair, line art and eyes look crisp with far less crunchy texture than a prior SwinFIR model
Training
- 41,893 anime images, from scratch, single RTX 4070 Ti SUPER 16GB, BF16 + torch.compile, 9.6GB VRAM
Fully open source: a ComfyUI node (via Manager) and weights on Hugging Face, with 1–4 loops selectable to trade speed for quality.
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