56 citations · 64 across the 10 of their papers we have counts for
12 papers
ACA-GS: Adaptive-Capacity Anchored Gaussian Splatting for Compact Dynamic Radiance Fields
Seunghyeon Song, Joo Chan Lee, Chanung Park +4
Recent advances in 4D Gaussian Splatting (4DGS) enable high-fidelity, real-time spatiotemporal rendering, but expose a fundamental trade-off between motion expressiveness and stora…
Optimized Minimal 4D Gaussian Splatting
Minseo Lee, Byeonghyeon Lee, Lucas Yunkyu Lee +7
4D Gaussian Splatting has emerged as a new paradigm for dynamic scene representation, enabling real-time rendering of scenes with complex motions. However, it faces a major challen…
TruncQuant: Truncation-Ready Quantization for DNNs with Flexible Weight Bit Precision
Jinhee Kim, Seoyeon Yoon, Taeho Lee +3
The deployment of deep neural networks on edge devices is a challenging task due to the increasing complexity of state-of-the-art models, requiring efforts to reduce model size and…
Single-step Diffusion for Image Compression at Ultra-Low Bitrates
Chanung Park, Joo Chan Lee, Jong Hwan Ko
Although there have been significant advancements in image compression techniques, such as standard and learned codecs, these methods still suffer from severe quality degradation a…
Optimized Minimal 3D Gaussian Splatting
Joo Chan Lee, Jong Hwan Ko, Eunbyung Park
3D Gaussian Splatting (3DGS) has emerged as a powerful representation for real-time, high-performance rendering, enabling a wide range of applications. However, representing 3D sce…
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…
F-3DGS: Factorized Coordinates and Representations for 3D Gaussian Splatting
Xiangyu Sun, Joo Chan Lee, Daniel Rho +3
The neural radiance field (NeRF) has made significant strides in representing 3D scenes and synthesizing novel views. Despite its advancements, the high computational costs of NeRF…
Continuous Memory Representation for Anomaly Detection
Joo Chan Lee, Taejune Kim, Eunbyung Park +2
There have been significant advancements in anomaly detection in an unsupervised manner, where only normal images are available for training. Several recent methods aim to detect a…
Coordinate-Aware Modulation for Neural Fields
Joo Chan Lee, Daniel Rho, Seungtae Nam +2
Neural fields, mapping low-dimensional input coordinates to corresponding signals, have shown promising results in representing various signals. Numerous methodologies have been pr…
Compact 3D Gaussian Representation for Radiance Field
Joo Chan Lee, Daniel Rho, Xiangyu Sun +2
Neural Radiance Fields (NeRFs) have demonstrated remarkable potential in capturing complex 3D scenes with high fidelity. However, one persistent challenge that hinders the widespre…
FFNeRV: Flow-Guided Frame-Wise Neural Representations for Videos
Joo Chan Lee, Daniel Rho, Jong Hwan Ko +1
Neural fields, also known as coordinate-based or implicit neural representations, have shown a remarkable capability of representing, generating, and manipulating various forms of…
Masked Wavelet Representation for Compact Neural Radiance Fields
Daniel Rho, Byeonghyeon Lee, Seungtae Nam +3
Neural radiance fields (NeRF) have demonstrated the potential of coordinate-based neural representation (neural fields or implicit neural representation) in neural rendering. Howev…