Binarization
145 papers with code • 16 benchmarks • 17 datasets
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Mini-Splatting: Representing Scenes with a Constrained Number of Gaussians
In this study, we explore the challenge of efficiently representing scenes with a constrained number of Gaussians.
FBPT: A Fully Binary Point Transformer
This paper presents a novel Fully Binary Point Cloud Transformer (FBPT) model which has the potential to be widely applied and expanded in the fields of robotics and mobile devices.
Method of Tracking and Analysis of Fluorescent-Labeled Cells Using Automatic Thresholding and Labeling
This paper presents a new method for efficiently tracking cells and quantitatively detecting the signal ratio between cytoplasm and nuclei.
Understanding Neural Network Binarization with Forward and Backward Proximal Quantizers
In neural network binarization, BinaryConnect (BC) and its variants are considered the standard.
DB-LLM: Accurate Dual-Binarization for Efficient LLMs
Large language models (LLMs) have significantly advanced the field of natural language processing, while the expensive memory and computation consumption impede their practical deployment.
ARBiBench: Benchmarking Adversarial Robustness of Binarized Neural Networks
2) BNNs consistently exhibit better adversarial robustness under black-box attacks.
When Input Integers are Given in the Unary Numeral Representation
These input integers are generally binarized, that is, provided in the form of the "binary" numeral representation, and the lengths of such binary forms are used as a basis unit to measure the computational complexity of the problems.
DocBinFormer: A Two-Level Transformer Network for Effective Document Image Binarization
Instead of using a simple vision transformer block to extract information from the image patches, the proposed architecture uses two transformer blocks for greater coverage of the extracted feature space on a global and local scale.
Signed Binarization: Unlocking Efficiency Through Repetition-Sparsity Trade-Off
Efficient inference of Deep Neural Networks (DNNs) on resource-constrained edge devices is essential.
BiHRNet: A Binary high-resolution network for Human Pose Estimation
On the challenging of COCO dataset, the proposed method enables the binary neural network to achieve 70. 8 mAP, which is better than most tested lightweight full-precision networks.