Search Results for author: Heung-Yeung Shum

Found 21 papers, 5 papers with code

HumanTOMATO: Text-aligned Whole-body Motion Generation

no code implementations19 Oct 2023 Shunlin Lu, Ling-Hao Chen, Ailing Zeng, Jing Lin, Ruimao Zhang, Lei Zhang, Heung-Yeung Shum

This work targets a novel text-driven whole-body motion generation task, which takes a given textual description as input and aims at generating high-quality, diverse, and coherent facial expressions, hand gestures, and body motions simultaneously.

Alpha-GPT: Human-AI Interactive Alpha Mining for Quantitative Investment

no code implementations31 Jul 2023 Saizhuo Wang, Hang Yuan, Leon Zhou, Lionel M. Ni, Heung-Yeung Shum, Jian Guo

One of the most important tasks in quantitative investment research is mining new alphas (effective trading signals or factors).

Prompt Engineering

Reinforced Disentanglement for Face Swapping without Skip Connection

no code implementations ICCV 2023 Xiaohang Ren, Xingyu Chen, Pengfei Yao, Heung-Yeung Shum, Baoyuan Wang

The SOTA face swap models still suffer the problem of either target identity (i. e., shape) being leaked or the target non-identity attributes (i. e., background, hair) failing to be fully preserved in the final results.

Disentanglement Face Swapping

Think-on-Graph: Deep and Responsible Reasoning of Large Language Model on Knowledge Graph

2 code implementations15 Jul 2023 Jiashuo Sun, Chengjin Xu, Lumingyuan Tang, Saizhuo Wang, Chen Lin, Yeyun Gong, Lionel M. Ni, Heung-Yeung Shum, Jian Guo

Although large language models (LLMs) have achieved significant success in various tasks, they often struggle with hallucination problems, especially in scenarios requiring deep and responsible reasoning.

Knowledge Graphs Language Modelling +2

Closed-Loop Transcription via Convolutional Sparse Coding

no code implementations18 Feb 2023 Xili Dai, Ke Chen, Shengbang Tong, Jingyuan Zhang, Xingjian Gao, Mingyang Li, Druv Pai, Yuexiang Zhai, Xiaojun Yuan, Heung-Yeung Shum, Lionel M. Ni, Yi Ma

Our method is arguably the first to demonstrate that a concatenation of multiple convolution sparse coding/decoding layers leads to an interpretable and effective autoencoder for modeling the distribution of large-scale natural image datasets.

Rolling Shutter Correction

Quant 4.0: Engineering Quantitative Investment with Automated, Explainable and Knowledge-driven Artificial Intelligence

no code implementations13 Dec 2022 Jian Guo, Saizhuo Wang, Lionel M. Ni, Heung-Yeung Shum

Quant has become one of the mainstream investment methodologies over the past decades, and has experienced three generations: Quant 1. 0, trading by mathematical modeling to discover mis-priced assets in markets; Quant 2. 0, shifting quant research pipeline from small ``strategy workshops'' to large ``alpha factories''; Quant 3. 0, applying deep learning techniques to discover complex nonlinear pricing rules.


Progressive Disentangled Representation Learning for Fine-Grained Controllable Talking Head Synthesis

1 code implementation CVPR 2023 Duomin Wang, Yu Deng, Zixin Yin, Heung-Yeung Shum, Baoyuan Wang

We present a novel one-shot talking head synthesis method that achieves disentangled and fine-grained control over lip motion, eye gaze&blink, head pose, and emotional expression.

Contrastive Learning Disentanglement

Learning Detailed Radiance Manifolds for High-Fidelity and 3D-Consistent Portrait Synthesis from Monocular Image

no code implementations CVPR 2023 Yu Deng, Baoyuan Wang, Heung-Yeung Shum

We introduce a novel detail manifolds reconstructor to learn 3D-consistent fine details on the radiance manifolds from monocular images, and combine them with the coarse radiance manifolds for high-fidelity reconstruction.

Image Generation Novel View Synthesis

Hand Avatar: Free-Pose Hand Animation and Rendering from Monocular Video

no code implementations CVPR 2023 Xingyu Chen, Baoyuan Wang, Heung-Yeung Shum

We present HandAvatar, a novel representation for hand animation and rendering, which can generate smoothly compositional geometry and self-occlusion-aware texture.


Statistical Foundation Behind Machine Learning and Its Impact on Computer Vision

no code implementations6 Sep 2022 Lei Zhang, Heung-Yeung Shum

This paper revisits the principle of uniform convergence in statistical learning, discusses how it acts as the foundation behind machine learning, and attempts to gain a better understanding of the essential problem that current deep learning algorithms are solving.

Representation Learning

On the Principles of Parsimony and Self-Consistency for the Emergence of Intelligence

no code implementations11 Jul 2022 Yi Ma, Doris Tsao, Heung-Yeung Shum

Ten years into the revival of deep networks and artificial intelligence, we propose a theoretical framework that sheds light on understanding deep networks within a bigger picture of Intelligence in general.

Semi-supervised 3D shape segmentation with multilevel consistency and part substitution

1 code implementation19 Apr 2022 Chun-Yu Sun, Yu-Qi Yang, Hao-Xiang Guo, Peng-Shuai Wang, Xin Tong, Yang Liu, Heung-Yeung Shum

We propose an effective semi-supervised method for learning 3D segmentations from a few labeled 3D shapes and a large amount of unlabeled 3D data.

Segmentation Semantic Segmentation +2

BIOS: An Algorithmically Generated Biomedical Knowledge Graph

no code implementations18 Mar 2022 Sheng Yu, Zheng Yuan, Jun Xia, Shengxuan Luo, Huaiyuan Ying, Sihang Zeng, Jingyi Ren, Hongyi Yuan, Zhengyun Zhao, Yucong Lin, Keming Lu, Jing Wang, Yutao Xie, Heung-Yeung Shum

For decades, these knowledge graphs have been developed via expert curation; however, this method can no longer keep up with today's AI development, and a transition to algorithmically generated BioMedKGs is necessary.

BIG-bench Machine Learning Knowledge Graphs +2

DINO: DETR with Improved DeNoising Anchor Boxes for End-to-End Object Detection

14 code implementations7 Mar 2022 Hao Zhang, Feng Li, Shilong Liu, Lei Zhang, Hang Su, Jun Zhu, Lionel M. Ni, Heung-Yeung Shum

Compared to other models on the leaderboard, DINO significantly reduces its model size and pre-training data size while achieving better results.

Real-Time Object Detection

Robust Conversational AI with Grounded Text Generation

no code implementations7 Sep 2020 Jianfeng Gao, Baolin Peng, Chunyuan Li, Jinchao Li, Shahin Shayandeh, Lars Liden, Heung-Yeung Shum

This article provides an overview of this progress and discusses related methods and technologies that can be incorporated for building robust conversational AI systems.

Text Generation World Knowledge

From Eliza to XiaoIce: Challenges and Opportunities with Social Chatbots

no code implementations6 Jan 2018 Heung-Yeung Shum, Xiaodong He, Di Li

Conversational systems have come a long way since their inception in the 1960s.


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