From the 1 of 6 linked papers with an AI index.
6 papers
Structure-Detail Decoupled Autoregressive Generation for Fast and High-Fidelity Virtual Try-On
Lu Yang, Xiaonan Hu, Yanan Li +3
The paper introduces STAR-VTON, a two‑stage autoregressive framework for virtual try‑on that generates garment structure in a latent space and then refines fine‑grained details in…
The Turning Point of 3D Plant Phenotyping: 3D Foundation Models Enable Minute-to-Second Cross-Crop Reconstruction and Beyond
Hanyue Jia, Wei Zhou, Wenbo Zhou +3
3D plant phenotyping is notoriously known to be procedure-complicated and of low throughput due to the extensive multi-view imaging, the fragile 3D reconstruction pipeline, and the…
DepthCropSeg++: Scaling a Crop Segmentation Foundation Model With Depth-Labeled Data
Jiafei Zhang, Songliang Cao, Binghui Xu +6
DepthCropSeg++: a foundation model for crop segmentation, capable of segmenting different crop species under open in-field environment. Crop segmentation is a fundamental task for…
Crowded Video Individual Counting Informed by Social Grouping and Spatial-Temporal Displacement Priors
Hao Lu, Xuhui Zhu, Wenjing Zhang +2
Video Individual Counting (VIC) is a recently introduced task aiming to estimate pedestrian flux from a video. It extends Video Crowd Counting (VCC) beyond the per-frame pedestrian…
FitControler: Toward Fit-Aware Virtual Try-On
Lu Yang, Yicheng Liu, Yanan Li +2
Realistic virtual try-on (VTON) concerns not only faithful rendering of garment details but also coordination of the style. Prior art typically pursues the former, but neglects a k…
TasselNetV4: A vision foundation model for cross-scene, cross-scale, and cross-species plant counting
Xiaonan Hu, Xuebing Li, Jinyu Xu +8
Accurate plant counting provides valuable information for agriculture such as crop yield prediction, plant density assessment, and phenotype quantification. Vision-based approaches…