README.md

metadata

title: 3D HAMSTER — 3D Trajectory Prediction
emoji: 🐹
colorFrom: blue
colorTo: green
sdk: gradio
sdk_version: 6.15.1
app_file: app.py
short_description: Predict metric 3D robot trajectories from RGB-D + language
python_version: '3.12'
startup_duration_timeout: 1h
pinned: false
license: apache-2.0
models:
  - DAVIAN-Robotics/3D_HAMSTER

🐹 3D HAMSTER — 3D Trajectory Prediction

Interactive demo for 3D HAMSTER, a depth-aware Vision-Language-Action planner that predicts metrically grounded 3D end-effector trajectories directly from a single RGB-D observation and a language instruction.

• Backbone: Qwen3-VL-8B + a frozen LingBot-Depth (DINOv2 ViT-L/14) geometry encoder.
• Inputs: RGB image + metric depth map (.npy, meters, aligned to RGB) + instruction.
• Outputs: [u, v, depth] waypoints + gripper actions, visualized as a 2D overlay and an interactive 3D scene + trajectory.
• Modes: 3D Trajectory (default), 2D Trajectory, 3D/2D Pointing, 2D Bounding Box, General VQA.

⚠️ Depth must be metric (meters) and aligned to the RGB frame.

Links: Paper · Model · Code · Project page