Encord debuts REACH egocentric hand-tracking model, cutting errors up to 70%
Scobleizer · x · 2026-11-06
Encord's AI team released Encord-REACH, an egocentric hand pose tracking model aimed at unlocking humanoid robot scaling in factories and homes.
- 30-70% lower error on industrial gloves in real-world egocentric video; wearer/bystander hand swaps nearly eliminated (0.5% vs 20%+ for other models)
- On standard 3D benchmarks, wrist error drops 80% and joint error 65% vs best published baselines
More from Embodied
- RAX lets coding agents unscrew a real jar with dexterous hands: 6 chained skills, 140° rotation — du_yilun · 2026-11-06
- HeLM: explicit language memory gives VLA robots +12.8 points on non-Markovian manipulation — SeoulNationalUniv · 2026-11-06
- 3 Years and Tens of Thousands of Lines of Code vs. One Prompt: AI Scene Generation's Leap — liliyu_lili · 2026-11-06
- UWaterloo 3D prints Invar36 flexures with directly mounted interferometer optics — jwt0625 · 2026-11-06
- LeRobot v0.7.0 ships as ecosystem passes 50,000 developers and 300+ organizations — LysandreJik · 2026-11-06
- Inside an SF AI-powered farm where AI runs operations, lighting and climate — Scobleizer · 2026-11-06