Search Results for author: Ji Hou

Found 16 papers, 10 papers with code

ControlRoom3D: Room Generation using Semantic Proxy Rooms

no code implementations8 Dec 2023 Jonas Schult, Sam Tsai, Lukas Höllein, Bichen Wu, Jialiang Wang, Chih-Yao Ma, Kunpeng Li, Xiaofang Wang, Felix Wimbauer, Zijian He, Peizhao Zhang, Bastian Leibe, Peter Vajda, Ji Hou

Central to our approach is a user-defined 3D semantic proxy room that outlines a rough room layout based on semantic bounding boxes and a textual description of the overall room style.

3D-CLFusion: Fast Text-to-3D Rendering with Contrastive Latent Diffusion

no code implementations21 Mar 2023 Yu-Jhe Li, Tao Xu, Ji Hou, Bichen Wu, Xiaoliang Dai, Albert Pumarola, Peizhao Zhang, Peter Vajda, Kris Kitani

We note that the novelty of our model lies in that we introduce contrastive learning during training the diffusion prior which enables the generation of the valid view-invariant latent code.

Contrastive Learning Text to 3D

Rotation-Invariant Transformer for Point Cloud Matching

1 code implementation CVPR 2023 Hao Yu, Zheng Qin, Ji Hou, Mahdi Saleh, Dongsheng Li, Benjamin Busam, Slobodan Ilic

To this end, we introduce RoITr, a Rotation-Invariant Transformer to cope with the pose variations in the point cloud matching task.

Data Augmentation Decoder

Mask3D: Pre-training 2D Vision Transformers by Learning Masked 3D Priors

no code implementations CVPR 2023 Ji Hou, Xiaoliang Dai, Zijian He, Angela Dai, Matthias Nießner

Current popular backbones in computer vision, such as Vision Transformers (ViT) and ResNets are trained to perceive the world from 2D images.

Contrastive Learning Instance Segmentation +6

PCR-CG: Point Cloud Registration via Deep Explicit Color and Geometry

1 code implementation28 Feb 2023 Yu Zhang, Junle Yu, Xiaolin Huang, Wenhui Zhou, Ji Hou

Different from previous methods that only use geometry representation, our module is specifically designed to effectively correlate color into geometry for the point cloud registration task.

Point Cloud Registration

RIGA: Rotation-Invariant and Globally-Aware Descriptors for Point Cloud Registration

1 code implementation27 Sep 2022 Hao Yu, Ji Hou, Zheng Qin, Mahdi Saleh, Ivan Shugurov, Kai Wang, Benjamin Busam, Slobodan Ilic

More specifically, 3D structures of the whole frame are first represented by our global PPF signatures, from which structural descriptors are learned to help geometric descriptors sense the 3D world beyond local regions.

Point Cloud Registration

Panoptic 3D Scene Reconstruction From a Single RGB Image

1 code implementation NeurIPS 2021 Manuel Dahnert, Ji Hou, Matthias Nießner, Angela Dai

Inspired by 2D panoptic segmentation, we propose to unify the tasks of geometric reconstruction, 3D semantic segmentation, and 3D instance segmentation into the task of panoptic 3D scene reconstruction - from a single RGB image, predicting the complete geometric reconstruction of the scene in the camera frustum of the image, along with semantic and instance segmentations.

3D Instance Segmentation 3D Scene Reconstruction +5

Pri3D: Can 3D Priors Help 2D Representation Learning?

1 code implementation ICCV 2021 Ji Hou, Saining Xie, Benjamin Graham, Angela Dai, Matthias Nießner

Inspired by these advances in geometric understanding, we aim to imbue image-based perception with representations learned under geometric constraints.

Contrastive Learning Instance Segmentation +5

Exploring Data-Efficient 3D Scene Understanding with Contrastive Scene Contexts

2 code implementations CVPR 2021 Ji Hou, Benjamin Graham, Matthias Nießner, Saining Xie

The rapid progress in 3D scene understanding has come with growing demand for data; however, collecting and annotating 3D scenes (e. g. point clouds) are notoriously hard.

3D Semantic Segmentation Instance Segmentation +2

RfD-Net: Point Scene Understanding by Semantic Instance Reconstruction

1 code implementation CVPR 2021 Yinyu Nie, Ji Hou, Xiaoguang Han, Matthias Nießner

In this work, we introduce RfD-Net that jointly detects and reconstructs dense object surfaces directly from raw point clouds.

Object object-detection +4

Deep Face Forgery Detection

1 code implementation6 Apr 2020 Nika Dogonadze, Jana Obernosterer, Ji Hou

Rapid progress in deep learning is continuously making it easier and cheaper to generate video forgeries.

Binary Classification Classification +3

RevealNet: Seeing Behind Objects in RGB-D Scans

no code implementations CVPR 2020 Ji Hou, Angela Dai, Matthias Nießner

Thus, we introduce the task of semantic instance completion: from an incomplete RGB-D scan of a scene, we aim to detect the individual object instances and infer their complete object geometry.

3D Reconstruction 3D Semantic Instance Segmentation +2

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