Object Mask

Object masks, representing the boundaries of objects within an image or video, are crucial for numerous computer vision tasks. Current research focuses on improving the accuracy, efficiency, and robustness of object mask generation and utilization, employing techniques like transformers, diffusion models, and attention mechanisms within various architectures such as Mask R-CNN and its variants. These advancements are driving progress in applications ranging from robotic grasping and augmented/virtual reality to video object segmentation and image inpainting, ultimately enhancing the capabilities of AI systems to interact with and understand the visual world.