11 papers · 1 filter
HOPE: A Memory-Based and Composition-Aware Framework for Zero-Shot Learning with Hopfield Network and Soft Mixture of Experts
Do Huu Dat, Po Yuan Mao, Tien Hoang Nguyen +2
Compositional Zero-Shot Learning (CZSL) has emerged as an essential paradigm in machine learning, aiming to overcome the constraints of traditional zero-shot learning by incorporat…
Dynamic Neural Surfaces for Elastic 4D Shape Representation and Analysis
Awais Nizamani, Hamid Laga, Guanjin Wang +3
We propose a novel framework for the statistical analysis of genus-zero 4D surfaces, i.e., 3D surfaces that deform and evolve over time. This problem is particularly challenging du…
Generalized Closed-form Formulae for Feature-based Subpixel Alignment in Patch-based Matching
Laurent Valentin Jospin, Farid Boussaid, Hamid Laga +1
Cost-based image patch matching is at the core of various techniques in computer vision, photogrammetry and remote sensing. When the subpixel disparity between the reference patch…
UIFormer: A Unified Transformer-based Framework for Incremental Few-Shot Object Detection and Instance Segmentation
Chengyuan Zhang, Yilin Zhang, Lei Zhu +6
This paper introduces a novel framework for unified incremental few-shot object detection (iFSOD) and instance segmentation (iFSIS) using the Transformer architecture. Our goal is…
Referring Human Pose and Mask Estimation in the Wild
Bo Miao, Mingtao Feng, Zijie Wu +3
We introduce Referring Human Pose and Mask Estimation (R-HPM) in the wild, where either a text or positional prompt specifies the person of interest in an image. This new task hold…
Temporally Consistent Referring Video Object Segmentation with Hybrid Memory
Bo Miao, Mohammed Bennamoun, Yongsheng Gao +2
Referring Video Object Segmentation (R-VOS) methods face challenges in maintaining consistent object segmentation due to temporal context variability and the presence of other visu…