Search Results for author:
Found 9 papers, 5 papers with code
FViT: A Focal Vision Transformer with Gabor Filter
Vision transformers have achieved encouraging progress in various computer vision tasks.
GraphTranslator: Aligning Graph Model to Large Language Model for Open-ended Tasks
Large language models (LLMs) like ChatGPT, exhibit powerful zero-shot and instruction-following capabilities, have catalyzed a revolutionary transformation across diverse fields, especially for open-ended tasks.
Optimize Individualized Energy Delivery for Septic Patients Using Predictive Deep Learning Models: A Real World Study
Excessive energy intake increased mortality rapidly in the early period of the acute phase.
EViT: An Eagle Vision Transformer with Bi-Fovea Self-Attention
Additionally, a Bionic Eagle Vision (BEV) block based on BFSA is designed in this study.
Box2Poly: Memory-Efficient Polygon Prediction of Arbitrarily Shaped and Rotated Text
Recently, Transformer-based text detection techniques have sought to predict polygons by encoding the coordinates of individual boundary vertices using distinct query features.
Primitive Graph Learning for Unified Vector Mapping
Then, we convert vector shape prediction, regularization, and topology reconstruction into a unique primitive graph learning problem.
MVLayoutNet:3D layout reconstruction with multi-view panoramas
We jointly train a layout module to produce an initial layout and a novel MVS module to obtain accurate layout geometry.
DeepLM: Large-Scale Nonlinear Least Squares on Deep Learning Frameworks Using Stochastic Domain Decomposition
We propose a novel approach for large-scale nonlinear least squares problems based on deep learning frameworks.
PrimitiveNet: Primitive Instance Segmentation With Local Primitive Embedding Under Adversarial Metric
We present PrimitiveNet, a novel approach for high-resolution primitive instance segmentation from point clouds on a large scale.
