Media Summary: Presentation Video for "Can Language Beat Numerical Regression? Language-Based Multimodal CaDeT: a Causal Disentanglement Approach for Robust Multiple Object Tracking (MOT) is a critical area within computer vision, with a broad spectrum of practical implementations.
Cvpr 2024 Singulartrajectory Universal Trajectory Predictor Using Diffusion Model - Detailed Analysis & Overview
Presentation Video for "Can Language Beat Numerical Regression? Language-Based Multimodal CaDeT: a Causal Disentanglement Approach for Robust Multiple Object Tracking (MOT) is a critical area within computer vision, with a broad spectrum of practical implementations. Video presentation of ECoDepth: Effective Conditioning of AirPlanes: Accurate Plane Estimation via 3D-Consistent Embeddings Jamie Watson, Filippo ... [CVPR 2025 U2Diff - Demo] Unified Uncertainty-Aware Diffusion for Multi-Agent Trajectory Modeling
Hakyeong Kim, Ruicheng Wang, Chengtang Yao, Jiaolong Yang, Min H. Kim (2026) “Dense Metric Depth Completion from ...