5 accepted papers
Point cloud completion aims to reconstruct complete 3D shapes from partial observations, which is a challenging problem due to severe occlusions and missing geometry. Despite recent advances in multimodal techniques that leverage complementary RGB images to compensate for missing geometry, most meth
In video-based point cloud compression (V-PCC), point clouds are generated as videos via patch projection to be compressed using video coding techniques. However, a large number of filled empty pixels in the videos creates a fake context, which reduces the noise prediction accuracy in compression ar…
Establishing robust policies is essential to counter attacks or disturbances affecting deep reinforcement learning (DRL) agents. Recent studies explore state-adversarial robustness and suggest the potential lack of an optimal robust policy (ORP), posing challenges in setting strict robustness constr…
The human vision system is highly adapted to extract structural information from the viewed scenes. The irregularity of point clouds makes the extraction of structural information containing both color and geometry an important challenge for point cloud quality assessment (PCQA). This paper proposes…
Weakly supervised temporal action localization aims to detect and localize actions in untrimmed videos with only video-level labels during training. However, without frame-level annotations, it is challenging to achieve localization completeness and relieve background interference. In this paper, we…