5 accepted papers
Many applications in Augmented/Virtual Reality or robotics require precise geometry modeling of individual elements in a dynamic scene under a sparse-view camera setup, without any prior information about their semantic labels or shapes. In our research, we introduce a 3D shape prior-free Neural Rad
Despite advancements in Neural Implicit models for 3D surface reconstruction, handling dynamic environments with interactions between arbitrary rigid, non-rigid, or deformable entities remains challenging. The generic reconstruction methods adaptable to such dynamic scenes often require additional i…
Holistic 3D human-scene reconstruction is a crucial and emerging research area in robot perception. A key challenge in holistic 3D human-scene reconstruction is to generate a physically plausible 3D scene from a single monocular RGB image. The existing research mainly proposes optimization-based app
Despite the significant progress in recent years, very few of the AI-based talking face generation methods attempt to render natural emotions. Moreover, the scope of the methods is majorly limited to the characteristics of the training dataset, hence they fail to generalize to arbitrary unseen faces…
Speech-driven facial animation methods should produce accurate and realistic lip motions with natural expressions and realistic texture portraying target-specific facial characteristics. Moreover, the methods should also be adaptable to any unknown faces and speech quickly during inference. Current…