3 citations · 6 across the 4 of their papers we have counts for
4 papers
Learning Human Motion from Monocular Videos via Cross-Modal Manifold Alignment
Shuaiying Hou, Hongyu Tao, Junheng Fang +3
Learning 3D human motion from 2D inputs is a fundamental task in the realms of computer vision and computer graphics. Many previous methods grapple with this inherently ambiguous t…
Manifold Path Guiding for Importance Sampling Specular Chains
Zhimin Fan, Pengpei Hong, Jie Guo +3
Complex visual effects such as caustics are often produced by light paths containing multiple consecutive specular vertices (dubbed specular chains), which pose a challenge to unbi…
CAP-VSTNet: Content Affinity Preserved Versatile Style Transfer
Linfeng Wen, Chengying Gao, Changqing Zou
Content affinity loss including feature and pixel affinity is a main problem which leads to artifacts in photorealistic and video style transfer. This paper proposes a new framewor…
MXM-CLR: A Unified Framework for Contrastive Learning of Multifold Cross-Modal Representations
Ye Wang, Bowei Jiang, Changqing Zou +1
Multifold observations are common for different data modalities, e.g., a 3D shape can be represented by multi-view images and an image can be described with different captions. Exi…