15 citations · 52 across the 6 of their papers we have counts for
8 papers
Semantic Segmentation under Adverse Conditions: A Weather and Nighttime-aware Synthetic Data-based Approach
Abdulrahman Kerim, Felipe Chamone, Washington Ramos +3
Recent semantic segmentation models perform well under standard weather conditions and sufficient illumination but struggle with adverse weather conditions and nighttime. Collectin…
Text-Driven Video Acceleration: A Weakly-Supervised Reinforcement Learning Method
Washington Ramos, Michel Silva, Edson Araujo +4
The growth of videos in our digital age and the users' limited time raise the demand for processing untrimmed videos to produce shorter versions conveying the same information. Des…
A Sparse Sampling-based framework for Semantic Fast-Forward of First-Person Videos
Michel Melo Silva, Washington Luis Souza Ramos, Mario Fernando Montenegro Campos +1
Technological advances in sensors have paved the way for digital cameras to become increasingly ubiquitous, which, in turn, led to the popularity of the self-recording culture. As…
Straight to the Point: Fast-forwarding Videos via Reinforcement Learning Using Textual Data
Washington Ramos, Michel Silva, Edson Araujo +2
The rapid increase in the amount of published visual data and the limited time of users bring the demand for processing untrimmed videos to produce shorter versions that convey the…
Personalizing Fast-Forward Videos Based on Visual and Textual Features from Social Network
Washington L. S. Ramos, Michel M. Silva, Edson R. Araujo +2
The growth of Social Networks has fueled the habit of people logging their day-to-day activities, and long First-Person Videos (FPVs) are one of the main tools in this new habit. S…
A Weighted Sparse Sampling and Smoothing Frame Transition Approach for Semantic Fast-Forward First-Person Videos
Michel Melo Silva, Washington Luis Souza Ramos, Joao Klock Ferreira +3
Thanks to the advances in the technology of low-cost digital cameras and the popularity of the self-recording culture, the amount of visual data on the Internet is going to the opp…