16 citations · 26 across the 8 of their papers we have counts for
9 papers
LACON: Training Text-to-Image Model from Uncurated Data
Zhiyang Liang, Ziyu Wan, Hongyu Liu +4
The success of modern text-to-image generation is largely attributed to massive, high-quality datasets. Currently, these datasets are curated through a filter-first paradigm that a…
Split-Layer: Enhancing Implicit Neural Representation by Maximizing the Dimensionality of Feature Space
Zhicheng Cai, Hao Zhu, Linsen Chen +2
Implicit neural representation (INR) models signals as continuous functions using neural networks, offering efficient and differentiable optimization for inverse problems across di…
Towards the Spectral bias Alleviation by Normalizations in Coordinate Networks
Zhicheng Cai, Hao Zhu, Qiu Shen +2
Representing signals using coordinate networks dominates the area of inverse problems recently, and is widely applied in various scientific computing tasks. Still, there exists an…
Encoding Semantic Priors into the Weights of Implicit Neural Representation
Zhicheng Cai, Qiu Shen
Implicit neural representation (INR) has recently emerged as a promising paradigm for signal representations, which takes coordinates as inputs and generates corresponding signal v…
RefConv: Re-parameterized Refocusing Convolution for Powerful ConvNets
Zhicheng Cai, Xiaohan Ding, Qiu Shen +1
We propose Re-parameterized Refocusing Convolution (RefConv) as a replacement for regular convolutional layers, which is a plug-and-play module to improve the performance without a…
Learn to Enhance the Negative Information in Convolutional Neural Network
Zhicheng Cai, Chenglei Peng, Qiu Shen
This paper proposes a learnable nonlinear activation mechanism specifically for convolutional neural network (CNN) termed as LENI, which learns to enhance the negative information…
FalconNet: Factorization for the Light-weight ConvNets
Zhicheng Cai, Qiu Shen
Designing light-weight CNN models with little parameters and Flops is a prominent research concern. However, three significant issues persist in the current light-weight CNNs: i) t…
Explore Spatio-temporal Aggregation for Insubstantial Object Detection: Benchmark Dataset and Baseline
Kailai Zhou, Yibo Wang, Tao Lv +4
We endeavor on a rarely explored task named Insubstantial Object Detection (IOD), which aims to localize the object with following characteristics: (1) amorphous shape with indisti…
FaceScape: 3D Facial Dataset and Benchmark for Single-View 3D Face Reconstruction
Hao Zhu, Haotian Yang, Longwei Guo +7
In this paper, we present a large-scale detailed 3D face dataset, FaceScape, and the corresponding benchmark to evaluate single-view facial 3D reconstruction. By training on FaceSc…