3 citations · 8 across the 19 of their papers we have counts for
8 papers · 1 filter
Improving the Robustness of 3D Human Pose Estimation: A Benchmark and Learning from Noisy Input
Trung-Hieu Hoang, Mona Zehni, Huy Phan +2
Despite the promising performance of current 3D human pose estimation techniques, understanding and enhancing their generalization on challenging in-the-wild videos remain an open…
EVCap: Retrieval-Augmented Image Captioning with External Visual-Name Memory for Open-World Comprehension
Jiaxuan Li, Duc Minh Vo, Akihiro Sugimoto +1
Large language models (LLMs)-based image captioning has the capability of describing objects not explicitly observed in training data; yet novel objects occur frequently, necessita…
A Compact Dynamic 3D Gaussian Representation for Real-Time Dynamic View Synthesis
Kai Katsumata, Duc Minh Vo, Hideki Nakayama
3D Gaussian Splatting (3DGS) has shown remarkable success in synthesizing novel views given multiple views of a static scene. Yet, 3DGS faces challenges when applied to dynamic sce…
Partition-and-Debias: Agnostic Biases Mitigation via A Mixture of Biases-Specific Experts
Jiaxuan Li, Duc Minh Vo, Hideki Nakayama
Bias mitigation in image classification has been widely researched, and existing methods have yielded notable results. However, most of these methods implicitly assume that a given…
Revisiting Latent Space of GAN Inversion for Real Image Editing
Kai Katsumata, Duc Minh Vo, Bei Liu +1
The exploration of the latent space in StyleGANs and GAN inversion exemplify impressive real-world image editing, yet the trade-off between reconstruction quality and editing quali…
Soft Curriculum for Learning Conditional GANs with Noisy-Labeled and Uncurated Unlabeled Data
Kai Katsumata, Duc Minh Vo, Tatsuya Harada +1
Label-noise or curated unlabeled data is used to compensate for the assumption of clean labeled data in training the conditional generative adversarial network; however, satisfying…