Seam Carving

Seam carving is a content-aware image and video resizing technique that removes or adds image regions based on their importance, preserving salient features while altering dimensions. Current research extends seam carving beyond 2D images, applying it to 3D models and neural radiance fields for tasks like shape augmentation and realistic 3D scene composition, often leveraging deep learning techniques for improved performance and automation. This approach finds applications in image editing, 3D modeling, and even image forensics, where detecting seam carving manipulation is crucial for verifying image authenticity.