4 citations · 5 across the 8 of their papers we have counts for
10 papers
ARGENT: Adaptive Hierarchical Image-Text Representations
Chuong Huynh, Hossein Souri, Abhinav Kumar +3
Large-scale Vision-Language Models (VLMs) such as CLIP learn powerful semantic representations but operate in Euclidean space, which fails to capture the inherent hierarchical stru…
Efficient and High-Fidelity Omni Modality Retrieval
Chuong Huynh, Manh Luong, Abhinav Shrivastava
Multimodal retrieval is the task of aggregating information from queries across heterogeneous modalities to retrieve desired targets. State-of-the-art multimodal retrieval models c…
All-in-One Conditioning for Text-to-Image Synthesis
Hirunima Jayasekara, Chuong Huynh, Yixuan Ren +2
Accurate interpretation and visual representation of complex prompts involving multiple objects, attributes, and spatial relationships is a critical challenge in text-to-image synt…
CoLLM: A Large Language Model for Composed Image Retrieval
Chuong Huynh, Jinyu Yang, Ashish Tawari +5
Composed Image Retrieval (CIR) is a complex task that aims to retrieve images based on a multimodal query. Typical training data consists of triplets containing a reference image,…
VeriGraph: Scene Graphs for Execution Verifiable Robot Planning
Daniel Ekpo, Mara Levy, Saksham Suri +3
Recent progress in vision-language models (VLMs) has opened new possibilities for robot task planning, but these models often produce incorrect action sequences. To address these l…
Composing Object Relations and Attributes for Image-Text Matching
Khoi Pham, Chuong Huynh, Ser-Nam Lim +1
We study the visual semantic embedding problem for image-text matching. Most existing work utilizes a tailored cross-attention mechanism to perform local alignment across the two i…
MaGGIe: Masked Guided Gradual Human Instance Matting
Chuong Huynh, Seoung Wug Oh, Abhinav Shrivastava +1
Human matting is a foundation task in image and video processing, where human foreground pixels are extracted from the input. Prior works either improve the accuracy by additional…
SimpSON: Simplifying Photo Cleanup with Single-Click Distracting Object Segmentation Network
Chuong Huynh, Yuqian Zhou, Zhe Lin +4
In photo editing, it is common practice to remove visual distractions to improve the overall image quality and highlight the primary subject. However, manually selecting and removi…
Progressive Semantic Segmentation
Chuong Huynh, Anh Tran, Khoa Luu +1
The objective of this work is to segment high-resolution images without overloading GPU memory usage or losing the fine details in the output segmentation map. The memory constrain…
Context Learning for Bone Shadow Exclusion in CheXNet Accuracy Improvement
Minh-Chuong Huynh, Trung-Hieu Nguyen, Minh-Triet Tran
Chest X-ray examination plays an important role in lung disease detection. The more accuracy of this task, the more experienced radiologists are required. After ChestX-ray14 datase…