I2PRef: Image-Driven Point Completion with Iterative Refinement

We present an image-conditioned point cloud completion approach that treats images as the primary geometric source rather than a secondary guide. To this end, we introduce an Image-to-Point (I2P) module that can reconstruct complete point clouds directly from a single RGB image, with no need for 3D inputs. Additionally, we introduce a transformer-based Point-to-Point (P2P) refinement module that uses self- and cross-attention between point tokens and image features to iteratively refine the coarse I2P output. The I2P module enables the image encoder to learn rich geometric representations, while the P2P module progressively recovers fine-grained details. Unlike existing multimodal methods that rely on auxiliary losses or fusion modules, our explicit I2P task provides a strong, geometry-aware prior based on images alone. Extensive experiments on ShapeNet-ViPC demonstrate state-of-the-art completion performance with a 12.3% relative Chamfer Distance improvement over prior methods. Code is available at: https://github.com/AzharSindhi/I2PRef.git

Improved Motion Plane Adaptive 360-Degree Video Compression Using Affine Motion Models

Efficient compression of 360-degree video content requires the application of advanced motion models for interframe prediction. The Motion Plane Adaptive (MPA) motion model projects the frames on multiple perspective planes in the 3D space. It improves the motion compensation by estimating the motion on those planes with a translational diamond search. In this work, we enhance this motion model with an affine parameterization and motion estimation method. Thereby, we find a feasible trade-off between the quality of the reconstructed frames and the computational cost. The affine motion estimation is hereby done with the inverse compositional Lucas-Kanade algorithm. With the proposed method, it is possible to improve the motion compensation significantly, so that the motion compensated frame has a Weighted-to-Spherically-uniform Peak Signal-to-Noise Ratio (WS-PSNR) which is about 1.6 dB higher than with the conventional MPA. In a basic video codec, the improved inter prediction can lead to Bj{\o}ntegaard Delta (BD) rate savings between 9 % and 35 % depending on the block size (BS) and number of motion parameters.