BARD-GS is a novel approach for robust dynamic scene reconstruction that effectively handles blurry inputs and imprecise camera poses.
A 19-dataset benchmark evaluating causal reasoning capabilities in vision models, revealing that performance drops sharply as causal complexity increases.
A unified ecosystem for evaluating embodied AI systems beyond coarse task success metrics, combining capability tests for fine-grained skill diagnosis and stress tests for robustness under real-world perturbations.
A real-time trajectory prediction framework that reformulates forecasting as a latent-space alignment problem. Achieves up to 54% faster adaptation and 9.9% higher accuracy across multiple autonomous driving benchmarks.
we introduce a novel RF editing pipeline that significantly enhances consistency by requiring the inpainting of only a single reference image. This image is then propagated across multiple views using a depth-based approach, to maintain consistencies.