The emergence of 3D Gaussian splatting (3DGS) has greatly accelerated rendering in novel
view synthesis. Unlike neural implicit representations like neural radiance fields (NeRFs) …

3D Gaussian Splatting (3DGS) has emerged as a prominent technique with the potential to
become a mainstream method for 3D representations. It can effectively transform multi-view …

Unsupervised video semantic compression (UVSC), ie, compressing videos to better
support various analysis tasks, has recently garnered attention. However, the semantic …

Aims Accurate heart function estimation is vital for detecting and monitoring cardiovascular
diseases. While two-dimensional echocardiography (2DE) is widely accessible and used, it …

Implicit Neural Representations (INRs) employ neural networks to approximate discrete data
as continuous functions. In the context of video data, such models can be utilized to …

Implicit Neural Representations (INRs) approximate discrete data through continuous
functions and are commonly used for encoding 2D images. Traditional image-based INRs …

The implicit neural representation (INR) employed in image compression shows high
decoding efficiency, yet it requires long encoding times due to the need for the model …

The recent development of 3D Gaussian Splatting (3DGS) has led to great interest in 4D
dynamic spatial reconstruction from multi-view visual inputs. While existing approaches …

Effective image tokenization is crucial for both multi-modal understanding and generation
tasks due to the necessity of the alignment with discrete text data. To this end, existing …

3D Gaussian Splatting (3DGS) has emerged as a pivotal technique for 3D scene
representation, providing rapid rendering speeds and high fidelity. As 3DGS gains …