View Consistency

View consistency in computer vision focuses on ensuring that representations of a 3D scene from multiple viewpoints are coherent and mutually reinforcing. Current research emphasizes developing algorithms and model architectures, such as neural radiance fields (NeRFs) and diffusion models, to achieve this consistency across various tasks, including 3D reconstruction, image generation, and autonomous driving perception. This work is crucial for improving the accuracy and robustness of many computer vision applications, particularly those relying on multi-sensor data or requiring the generation of realistic 3D models from 2D images. The resulting improvements in data quality and model performance have significant implications for fields like augmented and virtual reality, robotics, and medical imaging.