Artificial intelligence (AI) is evolving towards artificial general intelligence, which refers to the
ability of an AI system to perform a wide range of tasks and exhibit a level of intelligence …

The past decade has witnessed the rapid development and adoption of machine and deep
learning (ML & DL) methodologies in agricultural systems, showcased by great successes in …

Neural compression is the application of neural networks and other machine learning
methods to data compression. Recent advances in statistical machine learning have opened …

Zero-shot 6D object pose estimation involves the detection of novel objects with their 6D
poses in cluttered scenes presenting significant challenges for model generalizability …

Abstract The Segment Anything Model (SAM) is a recently developed large model for
general-purpose segmentation for computer vision tasks. SAM was trained using 11 million …

Abstract Weakly Supervised Semantic Segmentation (WSSS) aims to learn the concept of
segmentation using image-level class labels. Recent WSSS works have shown promising …

The evolution of video generation from text, starting with animating MNIST numbers to
simulating the physical world with Sora, has progressed at a breakneck speed over the past …

Abstract Zero-Shot Anomaly Segmentation (ZSAS) aims to segment anomalies without any
training data related to the test samples. Recently, while foundational models like CLIP and …

Segment anything model (SAM) has been widely applied to various downstream tasks for its
excellent performance and generalization capability. However, SAM exhibits three …

Multimodal large language models (MLLMs) equip pre-trained large-language models
(LLMs) with visual capabilities. While textual prompting in LLMs has been widely studied …