TrackCraft3R is the first method to repurpose a video diffusion transformer as a feed-forward dense 3D tracker via dual-latent representations and temporal RoPE alignment, achieving SOTA performance with lower compute.
Local all-pair correspondence for point tracking
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TrackCue uses dense image-space trajectories from point tracking and ego-motion compensation to improve static-dynamic classification and supervision for LiDAR scene flow estimation.
LingBot-Video is an open-source MoE video foundation model for embodied intelligence that scales to 120B parameters, integrates robot data, and uses multi-dimensional RL to improve physical plausibility.
citing papers explorer
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TrackCraft3R: Repurposing Video Diffusion Transformers for Dense 3D Tracking
TrackCraft3R is the first method to repurpose a video diffusion transformer as a feed-forward dense 3D tracker via dual-latent representations and temporal RoPE alignment, achieving SOTA performance with lower compute.
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Motion Cues from Image-based Point Tracking for LiDAR Scene Flow Estimation
TrackCue uses dense image-space trajectories from point tracking and ego-motion compensation to improve static-dynamic classification and supervision for LiDAR scene flow estimation.
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Scaling Mixture-of-Experts Video Pretraining for Embodied Intelligence
LingBot-Video is an open-source MoE video foundation model for embodied intelligence that scales to 120B parameters, integrates robot data, and uses multi-dimensional RL to improve physical plausibility.