#bev

2 articles

01 ·★ MEMBER·PAPER·12 min read Paper walkthrough: Qwen-Drive-1.0 — bolting 3D perception and planning onto a VLM without touching its architecture Leave the pretrained VLM exactly as it is, attach a BEV perception head and a Planning Expert, and you get 3D detection, occupancy, maps and trajectory generation in one model — general vision-language ability nearly intact, 90.7 PDMS on NAVSIM. A ground-up walkthrough, straight from the paper. 02 ·VLMs & Multimodal·★ MEMBER·PAPER·8 min read BEV Representations From Scratch — Fusing Multiple Cameras Into One Top-Down Map How a self-driving car turns six camera feeds into a single top-down map. Starting from perspective projection, we build up to the two big design philosophies: LSS, which pushes features into 3D via a predicted depth distribution, and Transformer-style methods like BEVFormer that pull information with BEV queries.