3 accepted papers
Recently, learning signed distance functions (SDFs) from point clouds has become popular for reconstruction. To ensure accuracy, most methods require using high-resolution Marching Cubes for surface extraction. However, this results in redundant mesh elements, making the mesh inconvenient to use. To…
Recently, there has been a growing interest in 3D CNN-based stereo matching methods due to their remarkable accuracy. However, the high complexity of 3D convolution makes it challenging to strike a balance between accuracy and speed. Notably, explicit 3D volumes contain considerable redundancy. In t…
Over the years, learning-based multi-view stereo methods have achieved great success based on their coarse-to-fine depth estimation frameworks. However, 3D CNN-based cost volume regularization inevitably leads to over-smoothing problems at object boundaries due to its smooth properties. Moreover, d…