GaussianImage: 1000 FPS Image Representation and Compression by 2D
  Gaussian Splatting
Implicit neural representations (INRs) recently achieved great success in
image representation and compression, offering high visual quality and fast
rendering speeds with 10-1000 FPS, assuming sufficient GPU resources are
available. However, this requirement often hinders their use on low-end devices
with limited memory. In response, we propose a groundbreaking paradigm of image
representation and compression by 2D Gaussian Splatting, named GaussianImage.
We first introduce 2D Gaussian to represent the image, where each Gaussian has
8 parameters including position, covariance and color. Subsequently, we unveil
a novel rendering algorithm based on accumulated summation. Remarkably, our
method with a minimum of 3times lower GPU memory usage and 5times faster
fitting time not only rivals INRs (e.g., WIRE, I-NGP) in representation
performance, but also delivers a faster rendering speed of 1500-2000 FPS
regardless of parameter size. Furthermore, we integrate existing vector
quantization technique to build an image codec. Experimental results
demonstrate that our codec attains rate-distortion performance comparable to
compression-based INRs such as COIN and COIN++, while facilitating decoding
speeds of approximately 1000 FPS. Additionally, preliminary proof of concept
shows that our codec surpasses COIN and COIN++ in performance when using
partial bits-back coding.
65f26d70addacd9d1219f16c
Xinjie Zhang
claimed_verified
2024-03-14T13:23:19.611Z
64338d1c4521083b9d2d21da
/avatars/54b809021d794f1c4b762fbc5d0c7c90.svg
Xinjie
user
Xinjie-Q
65f26d70addacd9d1219f16d
Xingtong Ge
admin_assigned
2024-03-14T08:47:05.721Z
65a94d2bbe0b2002351b6a8e
/avatars/c2a7a4bff254c643c1158a20dd74dc0f.svg
Xingtong Ge
user
domiso
65f26d70addacd9d1219f16e
Tongda Xu
admin_assigned
2024-03-14T08:47:11.605Z
64e805afd884b768fc610880
https://cdn-avatars.huggingface.co/v1/production/uploads/64e805afd884b768fc610880/VMfKuaXF6JLp2I2DDv3zH.png
tongda xu
user
xutongda
65f26d70addacd9d1219f16f
Dailan He
admin_assigned
2024-03-14T08:47:23.186Z
640622f3d6843690270e983d
/avatars/b76a40e460c72b90137262d597e8adbc.svg
Hedailan
user
Hedailan
65f26d70addacd9d1219f170
Yan Wang
65f26d70addacd9d1219f171
Hongwei Qin
admin_assigned
2024-03-14T08:47:37.678Z
6464a59a860abf0304961b60
/avatars/07c808426eb013990906624e2ffd1941.svg
Qin Hongwei
user
qin2023
65f26d70addacd9d1219f172
Guo Lu
65f26d70addacd9d1219f173
Jing Geng
65f26d70addacd9d1219f174
Jun Zhang
GaussianImage: 1000 FPS Image Representation and Compression by 2D
  Gaussian Splatting
Implicit neural representations (INRs) recently achieved great success in
image representation and compression, offering high visual quality and fast
rendering speeds with 10-1000 FPS, assuming sufficient GPU resources are
available. However, this requirement often hinders their use on low-end devices
with limited memory. In response, we propose a groundbreaking paradigm of image
representation and compression by 2D Gaussian Splatting, named GaussianImage.
We first introduce 2D Gaussian to represent the image, where each Gaussian has
8 parameters including position, covariance and color. Subsequently, we unveil
a novel rendering algorithm based on accumulated summation. Remarkably, our
method with a minimum of 3times lower GPU memory usage and 5times faster
fitting time not only rivals INRs (e.g., WIRE, I-NGP) in representation
performance, but also delivers a faster rendering speed of 1500-2000 FPS
regardless of parameter size. Furthermore, we integrate existing vector
quantization technique to build an image codec. Experimental results
demonstrate that our codec attains rate-distortion performance comparable to
compression-based INRs such as COIN and COIN++, while facilitating decoding
speeds of approximately 1000 FPS. Additionally, preliminary proof of concept
shows that our codec surpasses COIN and COIN++ in performance when using
partial bits-back coding.
Gaussian Splatting, a novel image representation and compression method, achieves high visual quality and fast rendering speeds with lower GPU memory usage and faster fitting time compared to existing INRs.
implicit neural representations 2D Gaussian Splatting GaussianImage rendering algorithm accumulated summation GPU memory usage fitting time WIRE I-NGP image codec vector quantization compression-based INRs COIN COIN++ rate-distortion performance partial bits-back coding