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Found 16 papers, 5 papers with code
SwiftAvatar: Efficient Auto-Creation of Parameterized Stylized Character on Arbitrary Avatar Engines
To this end, we propose SwiftAvatar, a novel avatar auto-creation framework that is evidently superior to previous works.
Multi-Granularity Distillation Scheme Towards Lightweight Semi-Supervised Semantic Segmentation
Consequently, we offer the first attempt to provide lightweight SSSS models via a novel multi-granularity distillation (MGD) scheme, where multi-granularity is captured from three aspects: i) complementary teacher structure; ii) labeled-unlabeled data cooperative distillation; iii) hierarchical and multi-levels loss setting.
Knowledge Distillation
Semi-Supervised Semantic Segmentation
Next-ViT: Next Generation Vision Transformer for Efficient Deployment in Realistic Industrial Scenarios
Then, Next Hybrid Strategy (NHS) is designed to stack NCB and NTB in an efficient hybrid paradigm, which boosts performance in various downstream tasks.
Ranked #253 on
Image Classification
on ImageNet
Parallel Pre-trained Transformers (PPT) for Synthetic Data-based Instance Segmentation
Recently, Synthetic data-based Instance Segmentation has become an exceedingly favorable optimization paradigm since it leverages simulation rendering and physics to generate high-quality image-annotation pairs.
MoCoViT: Mobile Convolutional Vision Transformer
Recently, Transformer networks have achieved impressive results on a variety of vision tasks.
TRT-ViT: TensorRT-oriented Vision Transformer
We revisit the existing excellent Transformers from the perspective of practical application.
Dressing in the Wild by Watching Dance Videos
While significant progress has been made in garment transfer, one of the most applicable directions of human-centric image generation, existing works overlook the in-the-wild imagery, presenting severe garment-person misalignment as well as noticeable degradation in fine texture details.
SepViT: Separable Vision Transformer
SepViT helps to carry out the information interaction within and among the windows via a depthwise separable self-attention.
ScalableViT: Rethinking the Context-oriented Generalization of Vision Transformer
The vanilla self-attention mechanism inherently relies on pre-defined and steadfast computational dimensions.
AlphaFold Accelerates Artificial Intelligence Powered Drug Discovery: Efficient Discovery of a Novel Cyclin-dependent Kinase 20 (CDK20) Small Molecule Inhibitor
The AlphaFold computer program predicted protein structures for the whole human genome, which has been considered as a remarkable breakthrough both in artificial intelligence (AI) application and structural biology.
Gaussian Context Transformer
These approaches commonly learn the relationship between global contexts and attention activations by using fully-connected layers or linear transformations.
Progressive Automatic Design of Search Space for One-Shot Neural Architecture Search
In this way, PAD-NAS can automatically design the operations for each layer and achieve a trade-off between search space quality and model diversity.
Linear Context Transform Block
In this work, we first revisit the SE block, and then present a detailed empirical study of the relationship between global context and attention distribution, based on which we propose a simple yet effective module, called Linear Context Transform (LCT) block.
Deep Learning for Multi-Scale Changepoint Detection in Multivariate Time Series
Many real-world time series, such as in health, have changepoints where the system's structure or parameters change.
Pyramid Recurrent Neural Networks for Multi-Scale Change-Point Detection
To address this, we show how changepoint detection can be treated as a supervised learning problem, and propose a new deep neural network architecture that can efficiently identify both abrupt and gradual changes at multiple scales.
DroidAnalytics: A Signature Based Analytic System to Collect, Extract, Analyze and Associate Android Malware
In this paper, we present the design and implementation of DroidAnalytics, a signature based analytic system to automatically collect, manage, analyze and extract android malware.
Cryptography and Security
