12 papers
UMamba: A Two-level Nested U-structure Mamba for Salient Object Detection
Junhui Li, Jialu Li, Youshan Zhang
Mamba-based models have emerged as a promising alternative for salient object detection (SOD), offering significant advantages in modeling long sequences. However, existing models…
FruitEnsemble: MLLM-Guided Arbitration for Heterogeneous ensemble in Fine-Grained Fruit Recognition
Enhui Yu, Junhui Li, Ruitong Lu +2
Fine-grained fruit classification is a critical yet challenging task in agricultural computer vision, primarily hindered by a severe shortage of high-quality datasets and the high…
Unifying VLM-Guided Flow Matching and Spectral Anomaly Detection for Interpretable Veterinary Diagnosis
Pu Wang, Zhixuan Mao, Jialu Li +3
Automatic diagnosis of canine pneumothorax is challenged by data scarcity and the need for trustworthy models. To address this, we first introduce a public, pixel-level annotated d…
Automatic Teaching Platform on Vision Language Retrieval Augmented Generation
Ruslan Gokhman, Jialu Li, Youshan Zhang
Automating teaching presents unique challenges, as replicating human interaction and adaptability is complex. Automated systems cannot often provide nuanced, real-time feedback tha…
SST-EM: Advanced Metrics for Evaluating Semantic, Spatial and Temporal Aspects in Video Editing
Varun Biyyala, Bharat Chanderprakash Kathuria, Jialu Li +1
Video editing models have advanced significantly, but evaluating their performance remains challenging. Traditional metrics, such as CLIP text and image scores, often fall short: t…
Leapfrog Latent Consistency Model (LLCM) for Medical Images Generation
Lakshmikar R. Polamreddy, Kalyan Roy, Sheng-Han Yueh +4
The scarcity of accessible medical image data poses a significant obstacle in effectively training deep learning models for medical diagnosis, as hospitals refrain from sharing the…
SparrowVQE: Visual Question Explanation for Course Content Understanding
Jialu Li, Manish Kumar Thota, Ruslan Gokhman +2
Visual Question Answering (VQA) research seeks to create AI systems to answer natural language questions in images, yet VQA methods often yield overly simplistic and short answers.…
Vision Transformer Segmentation for Visual Bird Sound Denoising
Sahil Kumar, Jialu Li, Youshan Zhang
Audio denoising, especially in the context of bird sounds, remains a challenging task due to persistent residual noise. Traditional and deep learning methods often struggle with ar…
Complex Image-Generative Diffusion Transformer for Audio Denoising
Junhui Li, Pu Wang, Jialu Li +1
The audio denoising technique has captured widespread attention in the deep neural network field. Recently, the audio denoising problem has been converted into an image generation…
Diffusion Gaussian Mixture Audio Denoise
Pu Wang, Junhui Li, Jialu Li +2
Recent diffusion models have achieved promising performances in audio-denoising tasks. The unique property of the reverse process could recover clean signals. However, the distribu…
DCHT: Deep Complex Hybrid Transformer for Speech Enhancement
Jialu Li, Junhui Li, Pu Wang +1
Most of the current deep learning-based approaches for speech enhancement only operate in the spectrogram or waveform domain. Although a cross-domain transformer combining waveform…
DPATD: Dual-Phase Audio Transformer for Denoising
Junhui Li, Pu Wang, Jialu Li +2
Recent high-performance transformer-based speech enhancement models demonstrate that time domain methods could achieve similar performance as time-frequency domain methods. However…