activity
20212024
most citedDeep Learning Techniques for In-Crop Weed Identification: A Review

80 citations · 85 across the 6 of their papers we have counts for

collaborators

6 papers

eess.IV2024

Identity-Consistent Diffusion Network for Grading Knee Osteoarthritis Progression in Radiographic Imaging

Wenhua Wu, Kun Hu, Wenxi Yue +5

Knee osteoarthritis (KOA), a common form of arthritis that causes physical disability, has become increasingly prevalent in society. Employing computer-aided techniques to automati…

cs.CV2024

Radio Frequency Signal based Human Silhouette Segmentation: A Sequential Diffusion Approach

Penghui Wen, Kun Hu, Dong Yuan +3

Radio frequency (RF) signals have been proved to be flexible for human silhouette segmentation (HSS) under complex environments. Existing studies are mainly based on a one-shot app…

cs.CV2024★ 2 cited

Motion Keyframe Interpolation for Any Human Skeleton via Temporally Consistent Point Cloud Sampling and Reconstruction

Clinton Mo, Kun Hu, Chengjiang Long +2

In the character animation field, modern supervised keyframe interpolation models have demonstrated exceptional performance in constructing natural human motions from sparse pose d…

cs.CV2023★ 2 cited

SurgicalPart-SAM: Part-to-Whole Collaborative Prompting for Surgical Instrument Segmentation

Wenxi Yue, Jing Zhang, Kun Hu +5

The Segment Anything Model (SAM) exhibits promise in generic object segmentation and offers potential for various applications. Existing methods have applied SAM to surgical instru…

cs.CV2023★ 1 cited

HGCLIP: Exploring Vision-Language Models with Graph Representations for Hierarchical Understanding

Peng Xia, Xingtong Yu, Ming Hu +4

Object categories are typically organized into a multi-granularity taxonomic hierarchy. When classifying categories at different hierarchy levels, traditional uni-modal approaches…

cs.CV2021★ 80 cited

Deep Learning Techniques for In-Crop Weed Identification: A Review

Kun Hu, Zhiyong Wang, Guy Coleman +6

Weeds are a significant threat to the agricultural productivity and the environment. The increasing demand for sustainable agriculture has driven innovations in accurate weed contr…