4 citations · 12 across the 22 of their papers we have counts for
10 papers · 1 filter
DINO Eats Geometry: Self-Supervised Sign Representations that Absorb Articulated Hand Geometry
Junyi Hu, Zhewen He, Haomian Huang +4
Handshape and orientation are geometric components of sign language, yet many sign encoders learn from appearance alone. We introduce SignDEG (DINO Eats Geometry), a temporal sign…
Focus Where It Counts: A Salience-Driven Vision-Language Model for Low Vision Assistance
Jiazhao Liang, Hao Huang, Shuaihang Yuan +8
Vision-language models (VLMs) are rapidly progressing and offer promising capabilities for assistive technologies supporting persons with blindness or low vision. However, existing…
VTaMo: Video-Text Alignment Model for Sign Language Translation
Junyi Hu, Zhewen He, Haomian Huang +2
Sign language translation (SLT) converts continuous sign videos into spoken language text. Gloss-free approaches leverage pre-trained visual encoders and language models but rely o…
SignNet-1M: Large-Scale Multilingual Sign Language Video Dataset with Downstream Benchmarks
Zhewen He, Junyi Hu, Haomian Huang +3
Sign language models are typically trained on datasets captured under constrained conditions, with limited viewpoint, background, and signer-identity diversity, leading to poor rob…
CurveFlow: Curvature-Guided Flow Matching for Image Generation
Yan Luo, Drake Du, Hao Huang +2
Existing rectified flow models are based on linear trajectories between data and noise distributions. This linearity enforces zero curvature, which can inadvertently force the imag…
A Chain-of-Thought Subspace Meta-Learning for Few-shot Image Captioning with Large Vision and Language Models
Hao Huang, Shuaihang Yuan, Yu Hao +2
A large-scale vision and language model that has been pretrained on massive data encodes visual and linguistic prior, which makes it easier to generate images and language that are…
Curvature Diversity-Driven Deformation and Domain Alignment for Point Cloud
Mengxi Wu, Hao Huang, Yi Fang +1
Unsupervised Domain Adaptation (UDA) is crucial for reducing the need for extensive manual data annotation when training deep networks on point cloud data. A significant challenge…
FairCLIP: Harnessing Fairness in Vision-Language Learning
Yan Luo, Min Shi, Muhammad Osama Khan +9
Fairness is a critical concern in deep learning, especially in healthcare, where these models influence diagnoses and treatment decisions. Although fairness has been investigated i…
A Multi-Modal Foundation Model to Assist People with Blindness and Low Vision in Environmental Interaction
Yu Hao, Fan Yang, Hao Huang +5
People with blindness and low vision (pBLV) encounter substantial challenges when it comes to comprehensive scene recognition and precise object identification in unfamiliar enviro…
Meta-Learning 3D Shape Segmentation Functions
Yu Hao, Hao Huang, Shuaihang Yuan +1
Learning robust 3D shape segmentation functions with deep neural networks has emerged as a powerful paradigm, offering promising performance in producing a consistent part segmenta…