Search Results for author:
Found 7 papers, 1 papers with code
CoGS: Controllable Gaussian Splatting
We present CoGS, a method for Controllable Gaussian Splatting, that enables the direct manipulation of scene elements, offering real-time control of dynamic scenes without the prerequisite of pre-computing control signals.
Zero-Shot Video Question Answering with Procedural Programs
We propose to answer zero-shot questions about videos by generating short procedural programs that derive a final answer from solving a sequence of visual subtasks.
Ranked #5 on
Zero-Shot Video Question Answer
on NExT-QA
Occlusion Sensitivity Analysis with Augmentation Subspace Perturbation in Deep Feature Space
In this study, we introduce the Occlusion Sensitivity Analysis with Deep Feature Augmentation Subspace (OSA-DAS), a novel perturbation-based interpretability approach for computer vision.
DyLiN: Making Light Field Networks Dynamic
Light Field Networks, the re-formulations of radiance fields to oriented rays, are magnitudes faster than their coordinate network counterparts, and provide higher fidelity with respect to representing 3D structures from 2D observations.
CoNFies: Controllable Neural Face Avatars
Neural Radiance Fields (NeRF) are compelling techniques for modeling dynamic 3D scenes from 2D image collections.
Adaptive occlusion sensitivity analysis for visually explaining video recognition networks
The key idea here is to occlude a specific volume of data by a 3D mask in an input 3D temporal-spatial data space and then measure the change degree in the output score.
Synthetic Expressions are Better Than Real for Learning to Detect Facial Actions
Critical obstacles in training classifiers to detect facial actions are the limited sizes of annotated video databases and the relatively low frequencies of occurrence of many actions.
