Search Results for author: James Davis

Found 18 papers, 1 papers with code

SplatFace: Gaussian Splat Face Reconstruction Leveraging an Optimizable Surface

no code implementations27 Mar 2024 Jiahao Luo, Jing Liu, James Davis

Our method is designed to simultaneously deliver both high-quality novel view rendering and accurate 3D mesh reconstructions.

3D Reconstruction Face Reconstruction +1

A Survey on Human-AI Teaming with Large Pre-Trained Models

no code implementations7 Mar 2024 Vanshika Vats, Marzia Binta Nizam, Minghao Liu, Ziyuan Wang, Richard Ho, Mohnish Sai Prasad, Vincent Titterton, Sai Venkat Malreddy, Riya Aggarwal, Yanwen Xu, Lei Ding, Jay Mehta, Nathan Grinnell, Li Liu, Sijia Zhong, Devanathan Nallur Gandamani, Xinyi Tang, Rohan Ghosalkar, Celeste Shen, Rachel Shen, Nafisa Hussain, Kesav Ravichandran, James Davis

In the rapidly evolving landscape of artificial intelligence (AI), the collaboration between human intelligence and AI systems, known as Human-AI (HAI) Teaming, has emerged as a cornerstone for advancing problem-solving and decision-making processes.

Decision Making

Assessing the Impact of Prompting Methods on ChatGPT's Mathematical Capabilities

no code implementations22 Dec 2023 Yuhao Chen, Chloe Wong, Hanwen Yang, Juan Aguenza, Sai Bhujangari, Benthan Vu, Xun Lei, Amisha Prasad, Manny Fluss, Eric Phuong, Minghao Liu, Raja Kumar, Vanshika Vats, James Davis

This study critically evaluates the efficacy of prompting methods in enhancing the mathematical reasoning capability of large language models (LLMs).

Chatbot GSM8K +4

Disjoint Pose and Shape for 3D Face Reconstruction

no code implementations26 Aug 2023 Raja Kumar, Jiahao Luo, Alex Pang, James Davis

Existing methods for 3D face reconstruction from a few casually captured images employ deep learning based models along with a 3D Morphable Model(3DMM) as face geometry prior.

3D Face Reconstruction Stereo Matching

Do humans and machines have the same eyes? Human-machine perceptual differences on image classification

no code implementations18 Apr 2023 Minghao Liu, Jiaheng Wei, Yang Liu, James Davis

Trained computer vision models are assumed to solve vision tasks by imitating human behavior learned from training labels.

Image Classification

Tag-based annotation creates better avatars

no code implementations14 Feb 2023 Minghao Liu, Zeyu Cheng, Shen Sang, Jing Liu, James Davis

Compared to direct annotation of labels, the proposed method: produces higher annotator agreements, causes machine learning to generates more consistent predictions, and only requires a marginal cost to add new rendering systems.


AgileAvatar: Stylized 3D Avatar Creation via Cascaded Domain Bridging

no code implementations15 Nov 2022 Shen Sang, Tiancheng Zhi, Guoxian Song, Minghao Liu, Chunpong Lai, Jing Liu, Xiang Wen, James Davis, Linjie Luo

We propose a novel self-supervised learning framework to create high-quality stylized 3D avatars with a mix of continuous and discrete parameters.

Self-Supervised Learning

Automated Rip Current Detection with Region based Convolutional Neural Networks

no code implementations4 Feb 2021 Akila de Silva, Issei Mori, Gregory Dusek, James Davis, Alex Pang

This paper presents a machine learning approach for the automatic identification of rip currents with breaking waves.

DuelGAN: A Duel Between Two Discriminators Stabilizes the GAN Training

no code implementations19 Jan 2021 Jiaheng Wei, Minghao Liu, Jiahao Luo, Andrew Zhu, James Davis, Yang Liu

In this paper, we introduce DuelGAN, a generative adversarial network (GAN) solution to improve the stability of the generated samples and to mitigate mode collapse.

Generative Adversarial Network Image Generation +1

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