Search Results for author: Mingyuan Zhang

Found 27 papers, 13 papers with code

Multiclass Learning from Noisy Labels for Non-decomposable Performance Measures

1 code implementation1 Feb 2024 Mingyuan Zhang, Shivani Agarwal

Most work on learning from noisy labels has focused on standard loss-based performance measures.

Information Retrieval

Multi-scale 2D Temporal Map Diffusion Models for Natural Language Video Localization

no code implementations16 Jan 2024 Chongzhi Zhang, Mingyuan Zhang, Zhiyang Teng, Jiayi Li, Xizhou Zhu, Lewei Lu, Ziwei Liu, Aixin Sun

Our method involves the direct generation of a global 2D temporal map via a conditional denoising diffusion process, based on the input video and language query.

Denoising Video Understanding

InsActor: Instruction-driven Physics-based Characters

no code implementations NeurIPS 2023 Jiawei Ren, Mingyuan Zhang, Cunjun Yu, Xiao Ma, Liang Pan, Ziwei Liu

Generating animation of physics-based characters with intuitive control has long been a desirable task with numerous applications.

Motion Planning

FineMoGen: Fine-Grained Spatio-Temporal Motion Generation and Editing

no code implementations NeurIPS 2023 Mingyuan Zhang, Huirong Li, Zhongang Cai, Jiawei Ren, Lei Yang, Ziwei Liu

Notably, FineMoGen further enables zero-shot motion editing capabilities with the aid of modern large language models (LLM), which faithfully manipulates motion sequences with fine-grained instructions.

Digital Life Project: Autonomous 3D Characters with Social Intelligence

no code implementations7 Dec 2023 Zhongang Cai, Jianping Jiang, Zhongfei Qing, Xinying Guo, Mingyuan Zhang, Zhengyu Lin, Haiyi Mei, Chen Wei, Ruisi Wang, Wanqi Yin, Xiangyu Fan, Han Du, Liang Pan, Peng Gao, Zhitao Yang, Yang Gao, Jiaqi Li, Tianxiang Ren, Yukun Wei, Xiaogang Wang, Chen Change Loy, Lei Yang, Ziwei Liu

In this work, we present Digital Life Project, a framework utilizing language as the universal medium to build autonomous 3D characters, who are capable of engaging in social interactions and expressing with articulated body motions, thereby simulating life in a digital environment.

Motion Captioning Motion Synthesis

On the Minimax Regret in Online Ranking with Top-k Feedback

no code implementations5 Sep 2023 Mingyuan Zhang, Ambuj Tewari

In online ranking, a learning algorithm sequentially ranks a set of items and receives feedback on its ranking in the form of relevance scores.

PointHPS: Cascaded 3D Human Pose and Shape Estimation from Point Clouds

no code implementations28 Aug 2023 Zhongang Cai, Liang Pan, Chen Wei, Wanqi Yin, Fangzhou Hong, Mingyuan Zhang, Chen Change Loy, Lei Yang, Ziwei Liu

To tackle these challenges, we propose a principled framework, PointHPS, for accurate 3D HPS from point clouds captured in real-world settings, which iteratively refines point features through a cascaded architecture.

3D human pose and shape estimation

BiBench: Benchmarking and Analyzing Network Binarization

1 code implementation26 Jan 2023 Haotong Qin, Mingyuan Zhang, Yifu Ding, Aoyu Li, Zhongang Cai, Ziwei Liu, Fisher Yu, Xianglong Liu

Network binarization emerges as one of the most promising compression approaches offering extraordinary computation and memory savings by minimizing the bit-width.

Benchmarking Binarization

MotionDiffuse: Text-Driven Human Motion Generation with Diffusion Model

2 code implementations31 Aug 2022 Mingyuan Zhang, Zhongang Cai, Liang Pan, Fangzhou Hong, Xinying Guo, Lei Yang, Ziwei Liu

Instead of a deterministic language-motion mapping, MotionDiffuse generates motions through a series of denoising steps in which variations are injected.

Denoising Motion Synthesis

AvatarCLIP: Zero-Shot Text-Driven Generation and Animation of 3D Avatars

1 code implementation17 May 2022 Fangzhou Hong, Mingyuan Zhang, Liang Pan, Zhongang Cai, Lei Yang, Ziwei Liu

Our key insight is to take advantage of the powerful vision-language model CLIP for supervising neural human generation, in terms of 3D geometry, texture and animation.

Language Modelling Motion Synthesis +1

Balanced MSE for Imbalanced Visual Regression

1 code implementation CVPR 2022 Jiawei Ren, Mingyuan Zhang, Cunjun Yu, Ziwei Liu

Data imbalance exists ubiquitously in real-world visual regressions, e. g., age estimation and pose estimation, hurting the model's generalizability and fairness.

Age Estimation Fairness +3

BiBERT: Accurate Fully Binarized BERT

1 code implementation ICLR 2022 Haotong Qin, Yifu Ding, Mingyuan Zhang, Qinghua Yan, Aishan Liu, Qingqing Dang, Ziwei Liu, Xianglong Liu

The large pre-trained BERT has achieved remarkable performance on Natural Language Processing (NLP) tasks but is also computation and memory expensive.


Playing for 3D Human Recovery

no code implementations14 Oct 2021 Zhongang Cai, Mingyuan Zhang, Jiawei Ren, Chen Wei, Daxuan Ren, Zhengyu Lin, Haiyu Zhao, Lei Yang, Chen Change Loy, Ziwei Liu

Specifically, we contribute GTA-Human, a large-scale 3D human dataset generated with the GTA-V game engine, featuring a highly diverse set of subjects, actions, and scenarios.

Bayesian Imbalanced Regression Debiasing

no code implementations29 Sep 2021 Jiawei Ren, Mingyuan Zhang, Cunjun Yu, Ziwei Liu

Compared to imbalanced and long-tailed classification, imbalanced regression has its unique challenges as the regression label space can be continuous, boundless, and high-dimensional.

Age Estimation imbalanced classification +2

Delving Deep into the Generalization of Vision Transformers under Distribution Shifts

1 code implementation CVPR 2022 Chongzhi Zhang, Mingyuan Zhang, Shanghang Zhang, Daisheng Jin, Qiang Zhou, Zhongang Cai, Haiyu Zhao, Xianglong Liu, Ziwei Liu

By comprehensively investigating these GE-ViTs and comparing with their corresponding CNN models, we observe: 1) For the enhanced model, larger ViTs still benefit more for the OOD generalization.

Out-of-Distribution Generalization Self-Supervised Learning

Towards Overcoming False Positives in Visual Relationship Detection

no code implementations23 Dec 2020 Daisheng Jin, Xiao Ma, Chongzhi Zhang, Yizhuo Zhou, Jiashu Tao, Mingyuan Zhang, Haiyu Zhao, Shuai Yi, Zhoujun Li, Xianglong Liu, Hongsheng Li

We observe that during training, the relationship proposal distribution is highly imbalanced: most of the negative relationship proposals are easy to identify, e. g., the inaccurate object detection, which leads to the under-fitting of low-frequency difficult proposals.

Graph Attention Human-Object Interaction Detection +4

REFINE: Prediction Fusion Network for Panoptic Segmentation

no code implementations15 Dec 2020 Jiawei Ren, Cunjun Yu, Zhongang Cai, Mingyuan Zhang, Chongsong Chen, Haiyu Zhao, Shuai Yi, Hongsheng Li

Panoptic segmentation aims at generating pixel-wise class and instance predictions for each pixel in the input image, which is a challenging task and far more complicated than naively fusing the semantic and instance segmentation results.

Instance Segmentation Panoptic Segmentation +1

Bayes Consistency vs. H-Consistency: The Interplay between Surrogate Loss Functions and the Scoring Function Class

no code implementations NeurIPS 2020 Mingyuan Zhang, Shivani Agarwal

When H is the class of linear models, the class F consists of certain piecewise linear scoring functions that are characterized by the same number of parameters as in the linear case, and minimization over which can be performed using an adaptation of the min-pooling idea from neural network training.

BiPointNet: Binary Neural Network for Point Clouds

1 code implementation ICLR 2021 Haotong Qin, Zhongang Cai, Mingyuan Zhang, Yifu Ding, Haiyu Zhao, Shuai Yi, Xianglong Liu, Hao Su

To alleviate the resource constraint for real-time point cloud applications that run on edge devices, in this paper we present BiPointNet, the first model binarization approach for efficient deep learning on point clouds.


Convex Calibrated Surrogates for the Multi-Label F-Measure

no code implementations ICML 2020 Mingyuan Zhang, Harish G. Ramaswamy, Shivani Agarwal

In particular, the F-measure explicitly balances recall (fraction of active labels predicted to be active) and precision (fraction of labels predicted to be active that are actually so), both of which are important in evaluating the overall performance of a multi-label classifier.

Multi-Label Classification

Foreseeing the Benefits of Incidental Supervision

2 code implementations EMNLP 2021 Hangfeng He, Mingyuan Zhang, Qiang Ning, Dan Roth

Real-world applications often require improved models by leveraging a range of cheap incidental supervision signals.

Informativeness Learning Theory +4

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