Search Results for author: Junran Peng

Found 26 papers, 8 papers with code

MaterialSeg3D: Segmenting Dense Materials from 2D Priors for 3D Assets

no code implementations22 Apr 2024 Zeyu Li, Ruitong Gan, Chuanchen Luo, Yuxi Wang, Jiaheng Liu, Ziwei Zhu Man Zhang, Qing Li, XuCheng Yin, Zhaoxiang Zhang, Junran Peng

Driven by powerful image diffusion models, recent research has achieved the automatic creation of 3D objects from textual or visual guidance.

CityGaussian: Real-time High-quality Large-Scale Scene Rendering with Gaussians

no code implementations1 Apr 2024 Yang Liu, He Guan, Chuanchen Luo, Lue Fan, Junran Peng, Zhaoxiang Zhang

The advancement of real-time 3D scene reconstruction and novel view synthesis has been significantly propelled by 3D Gaussian Splatting (3DGS).

3D Scene Reconstruction Novel View Synthesis

SAGD: Boundary-Enhanced Segment Anything in 3D Gaussian via Gaussian Decomposition

1 code implementation31 Jan 2024 Xu Hu, Yuxi Wang, Lue Fan, Junsong Fan, Junran Peng, Zhen Lei, Qing Li, Zhaoxiang Zhang

3D Gaussian Splatting has emerged as an alternative 3D representation for novel view synthesis, benefiting from its high-quality rendering results and real-time rendering speed.

Novel View Synthesis Segmentation +1

FurniScene: A Large-scale 3D Room Dataset with Intricate Furnishing Scenes

no code implementations7 Jan 2024 Genghao Zhang, Yuxi Wang, Chuanchen Luo, Shibiao Xu, Zhaoxiang Zhang, Man Zhang, Junran Peng

Indoor scene generation has attracted significant attention recently as it is crucial for applications of gaming, virtual reality, and interior design.

Scene Generation

LTA-PCS: Learnable Task-Agnostic Point Cloud Sampling

no code implementations CVPR 2024 Jiaheng Liu, Jianhao Li, Kaisiyuan Wang, Hongcheng Guo, Jian Yang, Junran Peng, Ke Xu, Xianglong Liu, Jinyang Guo

Existing task-agnostic point cloud sampling strategy (e. g. FPS) does not consider semantic information of point clouds causing degraded performance on downstream tasks.

HardMo: A Large-Scale Hardcase Dataset for Motion Capture

no code implementations CVPR 2024 Jiaqi Liao, Chuanchen Luo, Yinuo Du, Yuxi Wang, XuCheng Yin, Man Zhang, Zhaoxiang Zhang, Junran Peng

Empirically we find that the prediction failure in dance and martial arts is mainly characterized by the misalignment of hand-wrist and foot-ankle.

Human Mesh Recovery

FG-MDM: Towards Zero-Shot Human Motion Generation via Fine-Grained Descriptions

no code implementations5 Dec 2023 Xu Shi, Wei Yao, Chuanchen Luo, Junran Peng, Hongwen Zhang, Yunlian Sun

By adopting a divide-and-conquer strategy, we propose a new framework named Fine-Grained Human Motion Diffusion Model (FG-MDM) for zero-shot human motion generation.

Language Modelling Large Language Model

RoleLLM: Benchmarking, Eliciting, and Enhancing Role-Playing Abilities of Large Language Models

1 code implementation1 Oct 2023 Zekun Moore Wang, Zhongyuan Peng, Haoran Que, Jiaheng Liu, Wangchunshu Zhou, Yuhan Wu, Hongcheng Guo, Ruitong Gan, Zehao Ni, Jian Yang, Man Zhang, Zhaoxiang Zhang, Wanli Ouyang, Ke Xu, Stephen W. Huang, Jie Fu, Junran Peng

The advent of Large Language Models (LLMs) has paved the way for complex tasks such as role-playing, which enhances user interactions by enabling models to imitate various characters.

Benchmarking

DATA: Domain-Aware and Task-Aware Self-supervised Learning

1 code implementation CVPR 2022 Qing Chang, Junran Peng, Lingxie Xie, Jiajun Sun, Haoran Yin, Qi Tian, Zhaoxiang Zhang

However, due to the high training costs and the unconsciousness of downstream usages, most self-supervised learning methods lack the capability to correspond to the diversities of downstream scenarios, as there are various data domains, different vision tasks and latency constraints on models.

Image Classification Model Selection +5

GAIA: A Transfer Learning System of Object Detection that Fits Your Needs

1 code implementation CVPR 2021 Xingyuan Bu, Junran Peng, Junjie Yan, Tieniu Tan, Zhaoxiang Zhang

Transfer learning with pre-training on large-scale datasets has played an increasingly significant role in computer vision and natural language processing recently.

object-detection Object Detection +1

Uncertainty-Aware Pseudo Label Refinery for Domain Adaptive Semantic Segmentation

no code implementations ICCV 2021 Yuxi Wang, Junran Peng, Zhaoxiang Zhang

Unsupervised domain adaptation for semantic segmentation aims to assign the pixel-level labels for unlabeled target domain by transferring knowledge from the labeled source domain.

Pseudo Label Self-Supervised Learning +2

Efficient Neural Architecture Transformation Searchin Channel-Level for Object Detection

no code implementations5 Sep 2019 Junran Peng, Ming Sun, Zhao-Xiang Zhang, Tieniu Tan, Junjie Yan

With the combination of these two designs, an architecture transformation scheme could be discovered to adapt a network designed for image classification to task of object detection.

Image Classification Neural Architecture Search +3

POD: Practical Object Detection with Scale-Sensitive Network

no code implementations ICCV 2019 Junran Peng, Ming Sun, Zhao-Xiang Zhang, Tieniu Tan, Junjie Yan

Scale-sensitive object detection remains a challenging task, where most of the existing methods could not learn it explicitly and are not robust to scale variance.

Object object-detection +1

Accelerating Deep Neural Networks with Spatial Bottleneck Modules

no code implementations7 Sep 2018 Junran Peng, Lingxi Xie, Zhao-Xiang Zhang, Tieniu Tan, Jingdong Wang

This paper presents an efficient module named spatial bottleneck for accelerating the convolutional layers in deep neural networks.

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