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Found 12 papers, 2 papers with code
SA-GS: Scale-Adaptive Gaussian Splatting for Training-Free Anti-Aliasing
This integration is actually a limiting case of super-sampling, which significantly improves anti-aliasing performance over vanilla Gaussian Splatting.
Brain-inspired and Self-based Artificial Intelligence
In this paper, we introduce a Brain-inspired and Self-based Artificial Intelligence (BriSe AI) paradigm.
Efficient Training Spiking Neural Networks with Parallel Spiking Unit
Efficient parallel computing has become a pivotal element in advancing artificial intelligence.
A Survey on Deep Neural Network Partition over Cloud, Edge and End Devices
This paper provides a comprehensive survey on the recent advances and challenges in DNN partition approaches over the cloud, edge, and end devices based on a detailed literature collection.
An Efficient Knowledge Transfer Strategy for Spiking Neural Networks from Static to Event Domain
In order to improve the generalization ability of SNNs on event-based datasets, we use static images to assist SNN training on event data.
MSAT: Biologically Inspired Multi-Stage Adaptive Threshold for Conversion of Spiking Neural Networks
The self-adaptation to membrane potential and input allows a timely adjustment of the threshold to fire spike faster and transmit more information.
Spike Calibration: Fast and Accurate Conversion of Spiking Neural Network for Object Detection and Segmentation
Spiking neural network (SNN) has been attached to great importance due to the properties of high biological plausibility and low energy consumption on neuromorphic hardware.
Magic Pyramid: Accelerating Inference with Early Exiting and Token Pruning
To achieve this, we propose a novel idea, Magic Pyramid (MP), to reduce both width-wise and depth-wise computation via token pruning and early exiting for Transformer-based models, particularly BERT.
PAM: Understanding Product Images in Cross Product Category Attribute Extraction
Understanding product attributes plays an important role in improving online shopping experience for customers and serves as an integral part for constructing a product knowledge graph.
AutoKnow: Self-Driving Knowledge Collection for Products of Thousands of Types
Can one build a knowledge graph (KG) for all products in the world?
Non-Local Context Encoder: Robust Biomedical Image Segmentation against Adversarial Attacks
In this paper, we discover that global spatial dependencies and global contextual information in a biomedical image can be exploited to defend against adversarial attacks.
Non-locally Enhanced Encoder-Decoder Network for Single Image De-raining
Single image rain streaks removal has recently witnessed substantial progress due to the development of deep convolutional neural networks.
