Improved Hard Example Mining Approach For Single Shot Object Detectors

Aligned color and depth images allow exploring a scene by projecting the virtual camera to arbitrary positions. Depth-image-based rendering (DIBR) methods are often adopted in practical solutions, requiring fewer data than other approaches that explore stereo or multi-view setups. As the virtual camera moves, artifacts are expected to appear, which must be tackled adequately. For video sequences, not only spatial but also temporal inconsistencies affect the user experience. This paper proposes a background model that can be coupled to reduce the flickering of state-of-the-art still-image DIBR methods applied to video sequences captured by static cameras. Qualitative and quantitative results show the potential of the use of our method in practical applications.