lingbot-map
A feed-forward 3D foundation model for reconstructing scenes from streaming data
Debug pose drift in LingBot-MAP on custom video with unknown intrinsics. Learn to fix pseudo-intrinsics, undersampling, and frame ordering issues for accurate pose estimation.
Understanding the Trade‑offs Between `--keyframe_interval` and `--image_stride` for Long‑Sequence Processing in LingBotExplore the trade-offs between --keyframe_interval and --image_stride for long sequence processing in LingBot. Optimize GPU memory, throughput, and fidelity for streaming inference.
How LingBot-Map Handles Loop Closure Trajectories in Outdoor ScenesDiscover how LingBot-Map corrects drift in outdoor loop closure using anchor keyframes and trajectory memory. Learn how it re-attends to past locations for accurate pose estimation.
Understanding the `clean_kv_cache` Function in LingBot-Map: When to Manually Reset KV CachesLearn when to manually call LingBot-Map's clean_kv_cache function to reset KV caches, prevent stale attention, and avoid GPU memory issues in streaming models.
How to Configure Follow and Bird-Eye Camera Modes in a YAML Preset for Cinematic FlythroughsLearn to configure follow and birdeye camera modes in YAML presets for cinematic flythroughs in Ling-Bot Map. Master chase and aerial shots with easy parameter tuning.
How the skip_append Mechanism Enables Non-Keyframe Processing in Streaming InferenceLearn how the skip_append mechanism optimizes streaming inference by preventing non-keyframe KV pairs from caching, allowing models to attend to current frames without permanent storage.
GCTStream Model Architecture: Frame Blocks, Patch Embedding, and Global Blocks ExplainedExplore the GCTStream model architecture: Understand PatchEmbed for tokenization, frame_blocks for local processing, and global_blocks for temporal attention with KV caching. Unlock streaming vision transformer insights.
How to Add New Dataset Support to LingBot-Map’s Benchmark Evaluation FrameworkLearn to add new dataset support to LingBot-Map's benchmark evaluation framework. Subclass BaseDataset, implement data loading, register your class, and update config for seamless integration.
Why PyTorch 2.8.0 with CUDA 12.8 Is Required for the Batch Rendering Pipeline with KaolinDiscover why PyTorch 2.8.0 and CUDA 12.8 are essential for lingbot-map's batch rendering pipeline. Understand Kaolin's GPU acceleration and C++/CUDA extension needs.
How the `overlap_keyframes` Parameter Ensures Stable Pose Alignment Across Sliding WindowsDiscover how overlap_keyframes ensures stable pose alignment by converting keyframe units to frame counts, guaranteeing robust similarity transforms between sliding windows.
How `camera_num_iterations` Balances Pose Accuracy and Inference Speed in LingBot-MapExplore how camera_num_iterations impacts pose accuracy and inference speed in LingBot-Map. Understand the trade-offs for optimal performance in your Robbyant/lingbot-map project.
How to Optimize LingBot-MAP for Limited VRAM Using `--offload_to_cpu` and `--num_scale_frames`Optimize LingBot-MAP for limited VRAM by using --offload_to_cpu and --num_scale_frames. Reduce memory usage and maintain inference speed on your GPU.
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