In the field of visual scene understanding, deep neural networks have made impressive advancements in various core tasks like segmentation, tracking, and detection. However …
C Zhu, L Chen - IEEE Transactions on Pattern Analysis and …, 2024 - ieeexplore.ieee.org
As the most fundamental scene understanding tasks, object detection and segmentation have made tremendous progress in deep learning era. Due to the expensive manual …
Instance segmentation is data-hungry and as model capacity increases data scale becomes crucial for improving the accuracy. Most instance segmentation datasets today require costly …
Z Yang, F Zhan, K Liu, M Xu, S Lu - arXiv preprint arXiv:2310.01830, 2023 - arxiv.org
The advancement of visual intelligence is intrinsically tethered to the availability of data. In parallel, generative Artificial Intelligence (AI) has unlocked the potential to create synthetic …
The CLIP and Segment Anything Model (SAM) are remarkable vision foundation models (VFMs). SAM excels in segmentation tasks across diverse domains, while CLIP is renowned …
Open-vocabulary learning has emerged as a cutting-edge research area, particularly in light of the widespread adoption of vision-based foundational models. Its primary objective is to …
In-context segmentation has drawn more attention with the introduction of vision foundation models. Most existing approaches adopt metric learning or masked image modeling to build …
H Baek, S Yu, S Son, J Seo, Y Chung - Sensors, 2024 - mdpi.com
Due to the global population increase and the recovery of agricultural demand after the COVID-19 pandemic, the importance of agricultural automation and autonomous agricultural …
Recent advances in generative models, such as diffusion models, have made generating high-quality synthetic images widely accessible. Prior works have shown that training on …