Search Results for author:
Found 9 papers, 5 papers with code
Meta Episodic learning with Dynamic Task Sampling for CLIP-based Point Cloud Classification
In this direction, CLIP-based point cloud models like PointCLIP, CLIP2Point have become state-of-the-art methods in the few-shot setup.
Joint Visual Semantic Reasoning: Multi-Stage Decoder for Text Recognition
In this paper, we argue that semantic information offers a complementary role in addition to visual only.
Word-level Sign Language Recognition with Multi-stream Neural Networks Focusing on Local Regions
Thus in this work, we utilized local region images of both hands and face, along with skeletal information to capture local information and the positions of both hands relative to the body, respectively.
Ranked #2 on
Sign Language Recognition
on WLASL100
(using extra training data)
MetaHTR: Towards Writer-Adaptive Handwritten Text Recognition
In this paper, we take a completely different perspective -- we work on the assumption that there is always a new style that is drastically different, and that we will only have very limited data during testing to perform adaptation.
UDBNET: Unsupervised Document Binarization Network via Adversarial Game
In this paper, we present a novel approach towards document image binarization by introducing three-player min-max adversarial game.
Ranked #2 on
Binarization
on DIBCO 2011
Modeling Extent-of-Texture Information for Ground Terrain Recognition
Ground Terrain Recognition is a difficult task as the context information varies significantly over the regions of a ground terrain image.
A Deep One-Shot Network for Query-based Logo Retrieval
Logo detection in real-world scene images is an important problem with applications in advertisement and marketing.
User Constrained Thumbnail Generation using Adaptive Convolutions
We use Global Context Aggregation (GCA) and a modified Region Proposal Network (RPN) with adaptive convolutions to generate thumbnails in real time.
Fractional Local Neighborhood Intensity Pattern for Image Retrieval using Genetic Algorithm
The performance of the method has been tested for image retrieval on four popular databases.
