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9 papers · 2 filters
Videogenic: Identifying Highlight Moments in Videos with Professional Photographs as a Prior
David Chuan-En Lin, Fabian Caba Heilbron, Joon-Young Lee +2
This paper investigates the challenge of extracting highlight moments from videos. To perform this task, we need to understand what constitutes a highlight for arbitrary video doma…
Less is More: Consistent Video Depth Estimation with Masked Frames Modeling
Yiran Wang, Zhiyu Pan, Xingyi Li +3
Temporal consistency is the key challenge of video depth estimation. Previous works are based on additional optical flow or camera poses, which is time-consuming. By contrast, we d…
A Fast Text-Driven Approach for Generating Artistic Content
Marian Lupascu, Ryan Murdock, Ionut Mironica +1
In this work, we propose a complete framework that generates visual art. Unlike previous stylization methods that are not flexible with style parameters (i.e., they allow stylizati…
Towards Domain-agnostic Depth Completion
Guangkai Xu, Wei Yin, Jianming Zhang +4
Existing depth completion methods are often targeted at a specific sparse depth type and generalize poorly across task domains. We present a method to complete sparse/semi-dense, n…
Show Me What I Like: Detecting User-Specific Video Highlights Using Content-Based Multi-Head Attention
Uttaran Bhattacharya, Gang Wu, Stefano Petrangeli +2
We propose a method to detect individualized highlights for users on given target videos based on their preferred highlight clips marked on previous videos they have watched. Our m…
ANISE: Assembly-based Neural Implicit Surface rEconstruction
Dmitry Petrov, Matheus Gadelha, Radomir Mech +1
We present ANISE, a method that reconstructs a 3D~shape from partial observations (images or sparse point clouds) using a part-aware neural implicit shape representation. The shape…