19 citations · 25 across the 6 of their papers we have counts for
6 papers
SwiftTry: Fast and Consistent Video Virtual Try-On with Diffusion Models
Hung Nguyen, Quang Qui-Vinh Nguyen, Khoi Nguyen +1
Given an input video of a person and a new garment, the objective of this paper is to synthesize a new video where the person is wearing the specified garment while maintaining spa…
SharpDepth: Sharpening Metric Depth Predictions Using Diffusion Distillation
Duc-Hai Pham, Tung Do, Phong Nguyen +3
We propose SharpDepth, a novel approach to monocular metric depth estimation that combines the metric accuracy of discriminative depth estimation methods (e.g., Metric3D, UniDepth)…
Semi-supervised 3D Semantic Scene Completion with 2D Vision Foundation Model Guidance
Duc-Hai Pham, Duc-Dung Nguyen, Anh Pham +4
Accurate prediction of 3D semantic occupancy from 2D visual images is vital in enabling autonomous agents to comprehend their surroundings for planning and navigation. State-of-the…
PSENet: Progressive Self-Enhancement Network for Unsupervised Extreme-Light Image Enhancement
Hue Nguyen, Diep Tran, Khoi Nguyen +1
The extremes of lighting (e.g. too much or too little light) usually cause many troubles for machine and human vision. Many recent works have mainly focused on under-exposure cases…
Inductive and Transductive Few-Shot Video Classification via Appearance and Temporal Alignments
Khoi D. Nguyen, Quoc-Huy Tran, Khoi Nguyen +2
We present a novel method for few-shot video classification, which performs appearance and temporal alignments. In particular, given a pair of query and support videos, we conduct…
POODLE: Improving Few-shot Learning via Penalizing Out-of-Distribution Samples
Duong H. Le, Khoi D. Nguyen, Khoi Nguyen +3
In this work, we propose to use out-of-distribution samples, i.e., unlabeled samples coming from outside the target classes, to improve few-shot learning. Specifically, we exploit…