1 citations · 1 across the 6 of their papers we have counts for
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DanceCrafter: Fine-Grained Text-Driven Controllable Dance Generation via Choreographic Syntax
Hang Yuan, Xiaolin Hu, Yan Wan +8
Text-driven controllable dance generation remains under-explored, primarily due to the severe scarcity of high-quality datasets and the inherent difficulty of articulating complex…
Improving Neuropathological Reconstruction Fidelity via AI Slice Imputation
Marina Crespo Aguirre, Jonathan Williams-Ramirez, Dina Zemlyanker +13
Neuropathological analyses benefit from spatially precise volumetric reconstructions that enhance anatomical delineation and improve morphometric accuracy. Our prior work has shown…
2D Gaussians Meet Visual Tokenizer
Yiang Shi, Xiaoyang Guo, Wei Yin +5
The image tokenizer is a critical component in AR image generation, as it determines how rich and structured visual content is encoded into compact representations. Existing quanti…
Learning to Upscale 3D Segmentations in Neuroimaging
Xiaoling Hu, Peirong Liu, Dina Zemlyanker +3
Obtaining high-resolution (HR) segmentations from coarse annotations is a pervasive challenge in computer vision. Applications include inferring pixel-level segmentations from toke…
Learn2Synth: Learning Optimal Data Synthesis Using Hypergradients for Brain Image Segmentation
Xiaoling Hu, Xiangrui Zeng, Oula Puonti +3
Domain randomization through synthesis is a powerful strategy to train networks that are unbiased with respect to the domain of the input images. Randomization allows networks to s…
Learning Topological Representations for Deep Image Understanding
Xiaoling Hu
In many scenarios, especially biomedical applications, the correct delineation of complex fine-scaled structures such as neurons, tissues, and vessels is critical for downstream an…