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20222024
most citedCompact 3D Gaussian Splatting for Static and Dynamic Radiance Fields

3 citations · 6 across the 7 of their papers we have counts for

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cs.CV20243 cited

Compact 3D Gaussian Splatting for Static and Dynamic Radiance Fields

Joo Chan Lee, Daniel Rho, Xiangyu Sun +2

3D Gaussian splatting (3DGS) has recently emerged as an alternative representation that leverages a 3D Gaussian-based representation and introduces an approximated volumetric rende…

cs.CV2024

Freq-Mip-AA : Frequency Mip Representation for Anti-Aliasing Neural Radiance Fields

Youngin Park, Seungtae Nam, Cheul-hee Hahm +1

Neural Radiance Fields (NeRF) have shown remarkable success in representing 3D scenes and generating novel views. However, they often struggle with aliasing artifacts, especially w…

cs.CV20241 cited

Mip-Grid: Anti-aliased Grid Representations for Neural Radiance Fields

Seungtae Nam, Daniel Rho, Jong Hwan Ko +1

Despite the remarkable achievements of neural radiance fields (NeRF) in representing 3D scenes and generating novel view images, the aliasing issue, rendering "jaggies" or "blurry"…

cs.CV2024

Sharp-NeRF: Grid-based Fast Deblurring Neural Radiance Fields Using Sharpness Prior

Byeonghyeon Lee, Howoong Lee, Usman Ali +1

Neural Radiance Fields (NeRF) have shown remarkable performance in neural rendering-based novel view synthesis. However, NeRF suffers from severe visual quality degradation when th…

cs.CV2023

Hydra: Multi-head Low-rank Adaptation for Parameter Efficient Fine-tuning

Sanghyeon Kim, Hyunmo Yang, Younghyun Kim +2

The recent surge in large-scale foundation models has spurred the development of efficient methods for adapting these models to various downstream tasks. Low-rank adaptation method…

cs.CV20232 cited

SMPConv: Self-moving Point Representations for Continuous Convolution

Sanghyeon Kim, Eunbyung Park

Continuous convolution has recently gained prominence due to its ability to handle irregularly sampled data and model long-term dependency. Also, the promising experimental results…