1.9k citations · 3.4k across the 63 of their papers we have counts for
64 papers
Efficient Burst Raw Denoising with Variance Stabilization and Multi-frequency Denoising Network
Dasong Li, Yi Zhang, Ka Lung Law +3
With the growing popularity of smartphones, capturing high-quality images is of vital importance to smartphones. The cameras of smartphones have small apertures and small sensor ce…
RNNPose: Recurrent 6-DoF Object Pose Refinement with Robust Correspondence Field Estimation and Pose Optimization
Yan Xu, Kwan-Yee Lin, Guofeng Zhang +2
6-DoF object pose estimation from a monocular image is challenging, and a post-refinement procedure is generally needed for high-precision estimation. In this paper, we propose a f…
Learning a Structured Latent Space for Unsupervised Point Cloud Completion
Yingjie Cai, Kwan-Yee Lin, Chao Zhang +3
Unsupervised point cloud completion aims at estimating the corresponding complete point cloud of a partial point cloud in an unpaired manner. It is a crucial but challenging proble…
Point2Seq: Detecting 3D Objects as Sequences
Yujing Xue, Jiageng Mao, Minzhe Niu +5
We present a simple and effective framework, named Point2Seq, for 3D object detection from point clouds. In contrast to previous methods that normally {predict attributes of 3D obj…
IDR: Self-Supervised Image Denoising via Iterative Data Refinement
Yi Zhang, Dasong Li, Ka Lung Law +3
The lack of large-scale noisy-clean image pairs restricts supervised denoising methods' deployment in actual applications. While existing unsupervised methods are able to learn ima…
VL-LTR: Learning Class-wise Visual-Linguistic Representation for Long-Tailed Visual Recognition
Changyao Tian, Wenhai Wang, Xizhou Zhu +2
Deep learning-based models encounter challenges when processing long-tailed data in the real world. Existing solutions usually employ some balancing strategies or transfer learning…
INTERN: A New Learning Paradigm Towards General Vision
Jing Shao, Siyu Chen, Yangguang Li +24
Enormous waves of technological innovations over the past several years, marked by the advances in AI technologies, are profoundly reshaping the industry and the society. However,…
Rethinking Noise Synthesis and Modeling in Raw Denoising
Yi Zhang, Hongwei Qin, Xiaogang Wang +1
The lack of large-scale real raw image denoising dataset gives rise to challenges on synthesizing realistic raw image noise for training denoising models. However, the real raw ima…
FuseFormer: Fusing Fine-Grained Information in Transformers for Video Inpainting
Rui Liu, Hanming Deng, Yangyi Huang +6
Transformer, as a strong and flexible architecture for modelling long-range relations, has been widely explored in vision tasks. However, when used in video inpainting that require…
Voxel-based Network for Shape Completion by Leveraging Edge Generation
Xiaogang Wang, Marcelo H Ang, Gim Hee Lee
Deep learning technique has yielded significant improvements in point cloud completion with the aim of completing missing object shapes from partial inputs. However, most existing…
LIGA-Stereo: Learning LiDAR Geometry Aware Representations for Stereo-based 3D Detector
Xiaoyang Guo, Shaoshuai Shi, Xiaogang Wang +1
Stereo-based 3D detection aims at detecting 3D object bounding boxes from stereo images using intermediate depth maps or implicit 3D geometry representations, which provides a low-…
Fast Convergence of DETR with Spatially Modulated Co-Attention
Peng Gao, Minghang Zheng, Xiaogang Wang +2
The recently proposed Detection Transformer (DETR) model successfully applies Transformer to objects detection and achieves comparable performance with two-stage object detection f…
Scalable Transformers for Neural Machine Translation
Peng Gao, Shijie Geng, Yu Qiao +3
Transformer has been widely adopted in Neural Machine Translation (NMT) because of its large capacity and parallel training of sequence generation. However, the deployment of Trans…
DivCo: Diverse Conditional Image Synthesis via Contrastive Generative Adversarial Network
Rui Liu, Yixiao Ge, Ching Lam Choi +2
Conditional generative adversarial networks (cGANs) target at synthesizing diverse images given the input conditions and latent codes, but unfortunately, they usually suffer from t…
Pose-Controllable Talking Face Generation by Implicitly Modularized Audio-Visual Representation
Hang Zhou, Yasheng Sun, Wayne Wu +3
While accurate lip synchronization has been achieved for arbitrary-subject audio-driven talking face generation, the problem of how to efficiently drive the head pose remains. Prev…
Decoupled Spatial-Temporal Transformer for Video Inpainting
Rui Liu, Hanming Deng, Yangyi Huang +6
Video inpainting aims to fill the given spatiotemporal holes with realistic appearance but is still a challenging task even with prosperous deep learning approaches. Recent works i…
Visually Informed Binaural Audio Generation without Binaural Audios
Xudong Xu, Hang Zhou, Ziwei Liu +3
Stereophonic audio, especially binaural audio, plays an essential role in immersive viewing environments. Recent research has explored generating visually guided stereophonic audio…
Semantic Scene Completion via Integrating Instances and Scene in-the-Loop
Yingjie Cai, Xuesong Chen, Chao Zhang +3
Semantic Scene Completion aims at reconstructing a complete 3D scene with precise voxel-wise semantics from a single-view depth or RGBD image. It is a crucial but challenging probl…
Fixing the Teacher-Student Knowledge Discrepancy in Distillation
Jiangfan Han, Mengya Gao, Yujie Wang +3
Training a small student network with the guidance of a larger teacher network is an effective way to promote the performance of the student. Despite the different types, the guide…
Learning Fine-Grained Segmentation of 3D Shapes without Part Labels
Xiaogang Wang, Xun Sun, Xinyu Cao +2
Learning-based 3D shape segmentation is usually formulated as a semantic labeling problem, assuming that all parts of training shapes are annotated with a given set of tags. This a…
PV-RCNN++: Point-Voxel Feature Set Abstraction With Local Vector Representation for 3D Object Detection
Shaoshuai Shi, Li Jiang, Jiajun Deng +5
3D object detection is receiving increasing attention from both industry and academia thanks to its wide applications in various fields. In this paper, we propose Point-Voxel Regio…
Fast Convergence of DETR with Spatially Modulated Co-Attention
Peng Gao, Minghang Zheng, Xiaogang Wang +2
The recently proposed Detection Transformer (DETR) model successfully applies Transformer to objects detection and achieves comparable performance with two-stage object detection f…
Probabilistic Graph Attention Network with Conditional Kernels for Pixel-Wise Prediction
Dan Xu, Xavier Alameda-Pineda, Wanli Ouyang +3
Multi-scale representations deeply learned via convolutional neural networks have shown tremendous importance for various pixel-level prediction problems. In this paper we present…
A Holistically-Guided Decoder for Deep Representation Learning with Applications to Semantic Segmentation and Object Detection
Jianbo Liu, Sijie Ren, Yuanjie Zheng +2
Both high-level and high-resolution feature representations are of great importance in various visual understanding tasks. To acquire high-resolution feature maps with high-level s…