27 citations · 30 across the 6 of their papers we have counts for
8 papers
Visual Concept Connectome (VCC): Open World Concept Discovery and their Interlayer Connections in Deep Models
Matthew Kowal, Richard P. Wildes, Konstantinos G. Derpanis
Understanding what deep network models capture in their learned representations is a fundamental challenge in computer vision. We present a new methodology to understanding such vi…
Understanding Video Transformers via Universal Concept Discovery
Matthew Kowal, Achal Dave, Rares Ambrus +3
This paper studies the problem of concept-based interpretability of transformer representations for videos. Concretely, we seek to explain the decision-making process of video tran…
Reconstructive Latent-Space Neural Radiance Fields for Efficient 3D Scene Representations
Tristan Aumentado-Armstrong, Ashkan Mirzaei, Marcus A. Brubaker +4
Neural Radiance Fields (NeRFs) have proven to be powerful 3D representations, capable of high quality novel view synthesis of complex scenes. While NeRFs have been applied to graph…
GePSAn: Generative Procedure Step Anticipation in Cooking Videos
Mohamed Ashraf Abdelsalam, Samrudhdhi B. Rangrej, Isma Hadji +3
We study the problem of future step anticipation in procedural videos. Given a video of an ongoing procedural activity, we predict a plausible next procedure step described in rich…
Dual-Camera Joint Deblurring-Denoising
Shayan Shekarforoush, Amanpreet Walia, Marcus A. Brubaker +2
Recent image enhancement methods have shown the advantages of using a pair of long and short-exposure images for low-light photography. These image modalities offer complementary s…
StepFormer: Self-supervised Step Discovery and Localization in Instructional Videos
Nikita Dvornik, Isma Hadji, Ran Zhang +4
Instructional videos are an important resource to learn procedural tasks from human demonstrations. However, the instruction steps in such videos are typically short and sparse, wi…