6 citations · 14 across the 25 of their papers we have counts for
4 papers · 1 filter
World Models That Know When They Don't Know - Controllable Video Generation with Calibrated Uncertainty
Zhiting Mei, Tenny Yin, Micah Baker +2
Recent advances in generative video models have led to significant breakthroughs in high-fidelity video synthesis, specifically in controllable video generation where the generated…
Geometry Meets Vision: Revisiting Pretrained Semantics in Distilled Fields
Zhiting Mei, Ola Shorinwa, Anirudha Majumdar
Semantic distillation in radiance fields has spurred significant advances in open-vocabulary robot policies, e.g., in manipulation and navigation, founded on pretrained semantics f…
How Confident are Video Models? Empowering Video Models to Express their Uncertainty
Zhiting Mei, Ola Shorinwa, Anirudha Majumdar
Generative video models demonstrate impressive text-to-video capabilities, spurring widespread adoption in many real-world applications. However, like large language models (LLMs),…
FAST-Splat: Fast, Ambiguity-Free Semantics Transfer in Gaussian Splatting
Ola Shorinwa, Jiankai Sun, Mac Schwager
We present FAST-Splat for fast, ambiguity-free semantic Gaussian Splatting, which seeks to address the main limitations of existing semantic Gaussian Splatting methods, namely: slo…