4 citations · 5 across the 9 of their papers we have counts for
10 papers
Hybrid Gaussian Splatting for Novel Urban View Synthesis
Mohamed Omran, Farhad Zanjani, Davide Abati +2
This paper describes the Qualcomm AI Research solution to the RealADSim-NVS challenge, hosted at the RealADSim Workshop at ICCV 2025. The challenge concerns novel view synthesis in…
The 1st International Workshop on Disentangled Representation Learning for Controllable Generation (DRL4Real): Methods and Results
Qiuyu Chen, Xin Jin, Yue Song +45
This paper reviews the 1st International Workshop on Disentangled Representation Learning for Controllable Generation (DRL4Real), held in conjunction with ICCV 2025. The workshop a…
Scene-Aware Location Modeling for Data Augmentation in Automotive Object Detection
Jens Petersen, Davide Abati, Amirhossein Habibian +1
Generative image models are increasingly being used for training data augmentation in vision tasks. In the context of automotive object detection, methods usually focus on producin…
Gaussian Splatting is an Effective Data Generator for 3D Object Detection
Farhad G. Zanjani, Davide Abati, Auke Wiggers +4
We investigate data augmentation for 3D object detection in autonomous driving. We utilize recent advancements in 3D reconstruction based on Gaussian Splatting for 3D object placem…
Imagining the Unseen: Generative Location Modeling for Object Placement
Jooyeol Yun, Davide Abati, Mohamed Omran +3
Location modeling, or determining where non-existing objects could feasibly appear in a scene, has the potential to benefit numerous computer vision tasks, from automatic object in…
Object-Centric Diffusion for Efficient Video Editing
Kumara Kahatapitiya, Adil Karjauv, Davide Abati +3
Diffusion-based video editing have reached impressive quality and can transform either the global style, local structure, and attributes of given video inputs, following textual ed…
ResQ: Residual Quantization for Video Perception
Davide Abati, Haitam Ben Yahia, Markus Nagel +1
This paper accelerates video perception, such as semantic segmentation and human pose estimation, by levering cross-frame redundancies. Unlike the existing approaches, which avoid…
Delta Distillation for Efficient Video Processing
Amirhossein Habibian, Haitam Ben Yahia, Davide Abati +2
This paper aims to accelerate video stream processing, such as object detection and semantic segmentation, by leveraging the temporal redundancies that exist between video frames.…
Region-of-Interest Based Neural Video Compression
Yura Perugachi-Diaz, Guillaume Sautière, Davide Abati +3
Humans do not perceive all parts of a scene with the same resolution, but rather focus on few regions of interest (ROIs). Traditional Object-Based codecs take advantage of this bio…
Skip-Convolutions for Efficient Video Processing
Amirhossein Habibian, Davide Abati, Taco S. Cohen +1
We propose Skip-Convolutions to leverage the large amount of redundancies in video streams and save computations. Each video is represented as a series of changes across frames and…