10.9k citations
Counting papers with at most 25 authors, so collaboration author lists do not stand in for the people here.
- University of MichiganUS1.5k papers
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7 papers · 2 filters
HairPort: In-context 3D-aware Hair Import and Transfer for Images
Alireza Heidari, Amirhossein Alimohammadi, Ali Mahdavi-Amiri
Transferring hairstyles between images is an important but challenging task in computer graphics, computer vision, and visual effects. It enables users to explore new looks without…
MixerSENet: A Lightweight Framework for Efficient Hyperspectral Image Classification
Mohammed Q. Alkhatib, Swalpa Kumar Roy, Ali Jamali
In this paper, a novel framework, MixerSENet, is introduced for hyperspectral image (HSI) classification, designed to address the challenges of computational efficiency and limited…
Advances in Neural 3D Mesh Texturing: A Survey
Sai Raj Kishore Perla, Hao Zhang, Ali Mahdavi-Amiri
Texturing 3D meshes plays a vital role in determining the visual realism of digital objects and scenes. Although recent generative 3D approaches based on Neural Radiance Fields and…
MixerCA: An Efficient and Accurate Model for High-Performance Hyperspectral Image Classification
Mohammed Q. Alkhatib, Ali Jamali
Over the past decade, hyperspectral image (HSI) classification has drawn considerable interest due to HSIs' ability to effectively distinguish terrestrial objects by capturing deta…
Video Analysis and Generation via a Semantic Progress Function
Gal Metzer, Sagi Polaczek, Ali Mahdavi-Amiri +2
Transformations produced by image and video generation models often evolve in a highly non-linear manner: long stretches where the content barely changes are followed by sudden, ab…
TrackerSplat: Exploiting Point Tracking for Fast and Robust Dynamic 3D Gaussians Reconstruction
Daheng Yin, Isaac Ding, Yili Jin +2
Recent advancements in 3D Gaussian Splatting (3DGS) have demonstrated its potential for efficient and photorealistic 3D reconstructions, which is crucial for diverse applications s…
Lightweight Prompt-Guided CLIP Adaptation for Monocular Depth Estimation
Reyhaneh Ahani Manghotay, Jie Liang
Leveraging the rich semantic features of vision-language models (VLMs) like CLIP for monocular depth estimation tasks is a promising direction, yet often requires extensive fine-tu…