6 accepted papers
Generating realistic and diverse human-human interactions from text is a crucial yet challenging task in computer vision, graphics, and robotics. Despite recent advances, existing methods have two key limitations. First, two-person interaction synthesis is highly complex, simultaneously requiring in…
Faithfully reconstructing textured shapes and physical properties from videos presents an intriguing yet challenging problem. Significant efforts have been dedicated to advancing such a system identification problem in this area. Previous methods often rely on heavy optimization pipelines with a dif…
3D human generation is increasingly significant in various applications. However the direct use of 2D generative methods in 3D generation often results in losing local details while methods that reconstruct geometry from generated images struggle with global view consistency. In this work we introdu…
Human pose and shape (HPS) estimation with lensless imaging is not only beneficial to privacy protection but also can be used in covert surveillance scenarios due to the small size and simple structure of this device. However this task presents significant challenges due to the inherent ambiguity of…
3D human body representation learning has received increasing attention in recent years. However, existing works cannot flexibly, controllably and accurately represent human bodies, limited by coarse semantics and unsatisfactory representation capability, particularly in the absence of supervised da…
The advent of deep learning has led to significant progress in monocular human reconstruction. However, existing representations, such as parametric models, voxel grids, meshes and implicit neural representations, have difficulties achieving high-quality results and real-time speed at the same time.…