Results for “beamforming”

Trains, evaluates, and runs inference for BEVFusion multi-sensor 3D object detection models that fuse LiDAR and camera data in bird's-eye-view space for autonomous driving.

Train, evaluate, export, quantize, and run inference for a TAO OneFormer model that performs panoptic, instance, and semantic segmentation using task-conditioned queries.

Trains, evaluates, exports, quantizes, and runs inference for SegFormer semantic segmentation models using NVIDIA TAO.

Trains and fine-tunes vision models for object detection, image classification, and segmentation using Hugging Face Transformers on cloud GPUs, with automatic dataset validation and Hub persistence.

Trains, evaluates, exports, and runs inference for person re-identification models using TAO, learning discriminative embeddings for cross-camera matching.

Train, evaluate, export, quantize, and run inference on Mask2Former models for panoptic, instance, and semantic segmentation using NVIDIA TAO.

Build a single renderable HyperFrames composition using HTML with data-* timing attributes, clips, tracks, sub-compositions, variables, and deterministic rendering rules.

Creates, edits, and renders videos and animations from HTML compositions using the HyperFrames framework, handling project state, input adaptation, and workflow routing.

Provides atomic motion rules, multi-phase scene blueprints, scene transitions, motion-design techniques, and runtime adapters (GSAP, Lottie, Three.js, Anime.js, CSS, WAAPI, TypeGPU) for composing animations with HyperFrames.