1 citations · 1 across the 7 of their papers we have counts for
10 papers
MedCAGD: Context-Aware Gated Decoder for Efficient Medical Image Segmentation
Saad Wazir, Patrick Dominique Vibild, Dinh Phu Tran +2
Medical image segmentation relies on the ability of encoder-decoder architectures to translate rich feature representations into accurate pixel-level predictions under challenging…
FreqOrtho-SR: Frequency-Guided Orthogonal Expert Learning for Real-World Image Super-Resolution
Minh Son Hoang, Dinh Phu Tran, Quyen Nguyen Duc +2
Diffusion prior-based methods have shown impressive results in real-world image super-resolution (ISR), yet two key challenges persist: balancing pixel-level fidelity with semantic…
TB-AVA: Text as a Semantic Bridge for Audio-Visual Parameter Efficient Finetuning
Seongah Kim, Dinh Phu Tran, Hyeontaek Hwang +3
Audio-visual understanding requires effective alignment between heterogeneous modalities, yet cross-modal correspondence remains challenging when temporally aligned audio and visua…
SAT: Selective Aggregation Transformer for Image Super-Resolution
Dinh Phu Tran, Thao Do, Saad Wazir +3
Transformer-based approaches have revolutionized image super-resolution by modeling long-range dependencies. However, the quadratic computational complexity of vanilla self-attenti…
EnComp: Lightweight Encoder-Only Context Compression for Retrieval-Augmented Question Answering
Thao Do, Dinh Phu Tran, An Vo +2
Efficient context compression is critical for retrieval-augmented question answering in resource-constrained settings, where long retrieved contexts increase latency, memory use, a…
Knowing When to Answer: Adaptive Confidence Refinement for Reliable Audio-Visual Question Answering
Dinh Phu Tran, Jihoon Jeong, Saad Wazir +4
We present a formal problem formulation for \textit{Reliable} Audio-Visual Question Answering (-AVQA), where we prefer abstention over answering incorrectly. While rec…
VSRM: A Robust Mamba-Based Framework for Video Super-Resolution
Dinh Phu Tran, Dao Duy Hung, Daeyoung Kim
Video super-resolution remains a major challenge in low-level vision tasks. To date, CNN- and Transformer-based methods have delivered impressive results. However, CNNs are limited…
Reference-Based Post-OCR Processing with LLM for Precise Diacritic Text in Historical Document Recognition
Thao Do, Dinh Phu Tran, An Vo +1
Extracting fine-grained OCR text from aged documents in diacritic languages remains challenging due to unexpected artifacts, time-induced degradation, and lack of datasets. While s…
Channel-Partitioned Windowed Attention And Frequency Learning for Single Image Super-Resolution
Dinh Phu Tran, Dao Duy Hung, Daeyoung Kim
Recently, window-based attention methods have shown great potential for computer vision tasks, particularly in Single Image Super-Resolution (SISR). However, it may fall short in c…
Trans2Unet: Neural fusion for Nuclei Semantic Segmentation
Dinh-Phu Tran, Quoc-Anh Nguyen, Van-Truong Pham +1
Nuclei segmentation, despite its fundamental role in histopathological image analysis, is still a challenge work. The main challenge of this task is the existence of overlapping ar…