#dit

3 articles

01 ·★ MEMBER·PAPER·9 min read Paper Walkthrough: Marigold V2 — Turning an Image Editor Into a State-of-the-Art Depth Estimator on One 32GB GPU How Marigold V2 repurposes an image-editing diffusion transformer (Qwen-Image-Edit) into a state-of-the-art monocular depth estimator using QLoRA and two new losses — explained from first principles through normalization, single-step inference, iREPA, and SinkLoss. 02 ·★ MEMBER·PAPER·9 min read Paper Walkthrough: LLaDA-Image — Building the Visual Prior from Images Alone, Then Distilling to 2–4 Steps A training recipe that builds the visual prior from images alone before any caption enters the picture. We walk through LLaDA-Image — a 6B DiT trained from scratch and distilled down to 2–4 sampling steps — following the design decisions the paper actually makes. 03 ·FREE·PAPER·12 min read 4DAnyone, Explained — Turning One Casual Video Into a 4D Person How 4DAnyone builds a free-viewpoint 4D human from a single phone video, explained from scratch. The core trick is not a better generator but two fixes — RCP and TCR — for a context that no longer fits in one attention pass.