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HO-3D is a dataset providing image sequences of various hand-objectinteraction scenarios annotated with the 3D pose of the hand and the object andwas originally introduced as HO-3D_v2. The annotations were obtainedautomatically using an optimization method, 'HOnnotate', introduced in theoriginal paper. HO-3D_v3 provides more accurate annotations for both the handand object poses thus resulting in better estimates of contact regions betweenthe hand and the object. In this report, we elaborate on the improvements tothe HOnnotate method and provide evaluations to compare the accuracy ofHO-3D_v2 and HO-3D_v3. HO-3D_v3 results in 4mm higher accuracy compared toHO-3D_v2 for hand poses while exhibiting higher contact regions with the objectsurface.

HO-3D_v3: Improving the Accuracy of Hand-Object Annotations of the HO-3D Dataset