3results about How to "Reduce reconstruction error" patented technology

A video encoding and decoding method, apparatus, and medium are provided. An example method of video decoding includes receiving a video bitstream including a plurality of frames, the plurality of frames including a current frame; and identifying a primary reference frame for context initialization of the current frame. The method further includes identifying a reference frame of the current frame based on the primary reference frame, and reconstructing the current frame by applying a cross component sample offset (CCSO) mode using the reference frame.

This invention discloses a generative recommendation system and method based on quantized vector retrieval and LLM, belonging to the technical field of computer information processing and artificial intelligence recommendation systems. The method includes: Step S1, extracting continuous collaborative features of users and items; Step S2, constructing and pre-training an AHPQ segmenter quantization module, mapping continuous collaborative features to discrete ID token sequences and optimizing the quantized codebook; Step S3, using the pre-trained codebook vector to collaboratively initialize the LLM's token embedding layer; Step S4, fine-tuning the LLM using a freeze-adapt strategy, and then generating user preference vectors through a collaborative semantic fusion module; Step S5, calculating the similarity between the user preference vector and the item database vector, and retrieving Top-K items based on cosine similarity as the recommendation result. This invention solves the problems of ID discretization difficulties and collaborative signal loss in LLM recommendation, preserving the high-order collaborative structure while leveraging the semantic reasoning capabilities of LLM, and simultaneously achieving efficient reasoning and cold-start generalization.

This invention discloses a virtual skeleton perspective method, device, and storage medium, belonging to the field of medical image-assisted and computer vision-based 3D human body reconstruction technology. Addressing the shortcomings of existing medical imaging methods, such as the lack of visualization of the internal skeleton during positioning, poor real-time performance of iterative SKEL parameter solving, insufficient ability to measure real-world scales, and low reconstruction accuracy in occluded scenes, this invention replaces iterative optimization with a learned SKEL parameter estimation model, rapidly obtaining SKEL parameters through a single forward computation. The preferred scheme uses depth as a geometric prior to modulate attention, and adds bone length prediction to achieve metric scale recovery without internal parameters. Simultaneously, it realizes 3D skeleton virtual perspective overlay, positioning guidance, and real-world spatial distance measurement. This invention significantly improves the accuracy and efficiency of image positioning, reduces the radiation burden on patients, and balances reconstruction robustness and real-time performance.