Nov. 1, 2022, 1:15 a.m. | Azin Jahedi, Maximilian Luz, Lukas Mehl, Marc Rivinius, Andrés Bruhn

cs.CV updates on arXiv.org arxiv.org

In this report, we present our optical flow approach, MS-RAFT+, that won the
Robust Vision Challenge 2022. It is based on the MS-RAFT method, which
successfully integrates several multi-scale concepts into single-scale RAFT.
Our approach extends this method by exploiting an additional finer scale for
estimating the flow, which is made feasible by on-demand cost computation. This
way, it can not only operate at half the original resolution, but also use
MS-RAFT's shared convex upsampler to obtain full resolution flow. …

arxiv challenge raft scale vision

Software Engineer for AI Training Data (School Specific)

@ G2i Inc | Remote

Software Engineer for AI Training Data (Python)

@ G2i Inc | Remote

Software Engineer for AI Training Data (Tier 2)

@ G2i Inc | Remote

Data Engineer

@ Lemon.io | Remote: Europe, LATAM, Canada, UK, Asia, Oceania

Artificial Intelligence – Bioinformatic Expert

@ University of Texas Medical Branch | Galveston, TX

Lead Developer (AI)

@ Cere Network | San Francisco, US