Search Results for author:
Found 8 papers, 5 papers with code
Deep Convolutional Neural Network for 6-DOF Image Localization
We present an accurate and robust method for six degree of freedom image localization.
A Strong Baseline for Crowd Counting and Unsupervised People Localization
In this paper, we explore a strong baseline for crowd counting and an unsupervised people localization algorithm based on estimated density maps.
Coarse- and Fine-grained Attention Network with Background-aware Loss for Crowd Density Map Estimation
In this paper, we present a novel method Coarse- and Fine-grained Attention Network (CFANet) for generating high-quality crowd density maps and people count estimation by incorporating attention maps to better focus on the crowd area.
Entity Matching by Pool-based Active Learning
This method needs to manually label only a small number of valuable samples, and use these samples to build a model with high quality.
CoT-BERT: Enhancing Unsupervised Sentence Representation through Chain-of-Thought
Unsupervised sentence representation learning endeavors to transform input sentences into fixed-length vectors enriched with intricate semantic information while obviating the reliance on labeled data.
Simple Techniques for Enhancing Sentence Embeddings in Generative Language Models
Sentence Embedding stands as a fundamental task within the realm of Natural Language Processing, finding extensive application in search engines, expert systems, and question-and-answer platforms.
Short Text Topic Modeling with Topic Distribution Quantization and Negative Sampling Decoder
Topic models have been prevailing for many years on discovering latent semantics while modeling long documents.
