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Found 10 papers, 3 papers with code
Pest Manager: A Systematic Framework for Precise Pest Counting and Identification in Invisible Grain Pile Storage Environment
In this paper, we introduce a systematic framework: Pest Manager for precise pest counting and identification within the invisible grain pile environment.
Dual-Path Multi-Scale Transformer for High-Quality Image Deraining
Despite the superiority of convolutional neural networks (CNNs) and Transformers in single-image rain removal, current multi-scale models still face significant challenges due to their reliance on single-scale feature pyramid patterns.
RSDehamba: Lightweight Vision Mamba for Remote Sensing Satellite Image Dehazing
To this end, we propose the first lightweight network on the mamba-based model called RSDhamba in the field of RSID.
Single Stage Virtual Try-on via Deformable Attention Flows
Virtual try-on aims to generate a photo-realistic fitting result given an in-shop garment and a reference person image.
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Virtual Try-on
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M6-Fashion: High-Fidelity Multi-modal Image Generation and Editing
The fashion industry has diverse applications in multi-modal image generation and editing.
In-N-Out Generative Learning for Dense Unsupervised Video Segmentation
By contrast, pixel-level optimization is more explicit, however, it is sensitive to the visual quality of training data and is not robust to object deformation.
Cross-domain User Preference Learning for Cold-start Recommendation
With user history represented by a domain-aware sequential model, a frequency encoder is applied to the underlying tags for user content preference learning.
M6: A Chinese Multimodal Pretrainer
In this work, we construct the largest dataset for multimodal pretraining in Chinese, which consists of over 1. 9TB images and 292GB texts that cover a wide range of domains.
Network Clustering for Multi-task Learning
The majority of current MTL studies adopt the hard parameter sharing structure, where hard layers tend to learn general representations over all tasks and specific layers are prone to learn specific representations for each task.
Deep Hierarchical Classification for Category Prediction in E-commerce System
In e-commerce system, category prediction is to automatically predict categories of given texts.
