3.2k citations · 12.3k across the 227 of their papers we have counts for
34 papers · 1 filter
Chasing the Tail in Monocular 3D Human Reconstruction with Prototype Memory
Yu Rong, Ziwei Liu, Chen Change Loy
Deep neural networks have achieved great progress in single-image 3D human reconstruction. However, existing methods still fall short in predicting rare poses. The reason is that m…
Computation-Efficient Knowledge Distillation via Uncertainty-Aware Mixup
Guodong Xu, Ziwei Liu, Chen Change Loy
Knowledge distillation, which involves extracting the "dark knowledge" from a teacher network to guide the learning of a student network, has emerged as an essential technique for…
Positional Encoding as Spatial Inductive Bias in GANs
Rui Xu, Xintao Wang, Kai Chen +2
SinGAN shows impressive capability in learning internal patch distribution despite its limited effective receptive field. We are interested in knowing how such a translation-invari…
CARAFE++: Unified Content-Aware ReAssembly of FEatures
Jiaqi Wang, Kai Chen, Rui Xu +3
Feature reassembly, i.e. feature downsampling and upsampling, is a key operation in a number of modern convolutional network architectures, e.g., residual networks and feature pyra…
Focal Frequency Loss for Image Reconstruction and Synthesis
Liming Jiang, Bo Dai, Wayne Wu +1
Image reconstruction and synthesis have witnessed remarkable progress thanks to the development of generative models. Nonetheless, gaps could still exist between the real and gener…
Exploring Data Augmentation for Multi-Modality 3D Object Detection
Wenwei Zhang, Zhe Wang, Chen Change Loy
It is counter-intuitive that multi-modality methods based on point cloud and images perform only marginally better or sometimes worse than approaches that solely use point cloud. T…
BasicVSR: The Search for Essential Components in Video Super-Resolution and Beyond
Kelvin C. K. Chan, Xintao Wang, Ke Yu +2
Video super-resolution (VSR) approaches tend to have more components than the image counterparts as they need to exploit the additional temporal dimension. Complex designs are not…
GLEAN: Generative Latent Bank for Large-Factor Image Super-Resolution
Kelvin C. K. Chan, Xintao Wang, Xiangyu Xu +2
We show that pre-trained Generative Adversarial Networks (GANs), e.g., StyleGAN, can be used as a latent bank to improve the restoration quality of large-factor image super-resolut…
Do 2D GANs Know 3D Shape? Unsupervised 3D shape reconstruction from 2D Image GANs
Xingang Pan, Bo Dai, Ziwei Liu +2
Natural images are projections of 3D objects on a 2D image plane. While state-of-the-art 2D generative models like GANs show unprecedented quality in modeling the natural image man…
Flexible Piecewise Curves Estimation for Photo Enhancement
Chongyi Li, Chunle Guo, Qiming Ai +2
This paper presents a new method, called FlexiCurve, for photo enhancement. Unlike most existing methods that perform image-to-image mapping, which requires expensive pixel-wise re…
Understanding Deformable Alignment in Video Super-Resolution
Kelvin C. K. Chan, Xintao Wang, Ke Yu +2
Deformable convolution, originally proposed for the adaptation to geometric variations of objects, has recently shown compelling performance in aligning multiple frames and is incr…
Texture Memory-Augmented Deep Patch-Based Image Inpainting
Rui Xu, Minghao Guo, Jiaqi Wang +3
Patch-based methods and deep networks have been employed to tackle image inpainting problem, with their own strengths and weaknesses. Patch-based methods are capable of restoring a…
Delving into Inter-Image Invariance for Unsupervised Visual Representations
Jiahao Xie, Xiaohang Zhan, Ziwei Liu +2
Contrastive learning has recently shown immense potential in unsupervised visual representation learning. Existing studies in this track mainly focus on intra-image invariance lear…
Seesaw Loss for Long-Tailed Instance Segmentation
Jiaqi Wang, Wenwei Zhang, Yuhang Zang +7
Instance segmentation has witnessed a remarkable progress on class-balanced benchmarks. However, they fail to perform as accurately in real-world scenarios, where the category dist…
MessyTable: Instance Association in Multiple Camera Views
Zhongang Cai, Junzhe Zhang, Daxuan Ren +5
We present an interesting and challenging dataset that features a large number of scenes with messy tables captured from multiple camera views. Each scene in this dataset is highly…
TSIT: A Simple and Versatile Framework for Image-to-Image Translation
Liming Jiang, Changxu Zhang, Mingyang Huang +3
We introduce a simple and versatile framework for image-to-image translation. We unearth the importance of normalization layers, and provide a carefully designed two-stream generat…
LiteFlowNet3: Resolving Correspondence Ambiguity for More Accurate Optical Flow Estimation
Tak-Wai Hui, Chen Change Loy
Deep learning approaches have achieved great success in addressing the problem of optical flow estimation. The keys to success lie in the use of cost volume and coarse-to-fine flow…
RGB-D Salient Object Detection with Cross-Modality Modulation and Selection
Chongyi Li, Runmin Cong, Yongri Piao +2
We present an effective method to progressively integrate and refine the cross-modality complementarities for RGB-D salient object detection (SOD). The proposed network mainly solv…
Knowledge Distillation Meets Self-Supervision
Guodong Xu, Ziwei Liu, Xiaoxiao Li +1
Knowledge distillation, which involves extracting the "dark knowledge" from a teacher network to guide the learning of a student network, has emerged as an important technique for…
Online Deep Clustering for Unsupervised Representation Learning
Xiaohang Zhan, Jiahao Xie, Ziwei Liu +2
Joint clustering and feature learning methods have shown remarkable performance in unsupervised representation learning. However, the training schedule alternating between feature…
Cross-Scale Internal Graph Neural Network for Image Super-Resolution
Shangchen Zhou, Jiawei Zhang, Wangmeng Zuo +1
Non-local self-similarity in natural images has been well studied as an effective prior in image restoration. However, for single image super-resolution (SISR), most existing deep…
Inter-Region Affinity Distillation for Road Marking Segmentation
Yuenan Hou, Zheng Ma, Chunxiao Liu +2
We study the problem of distilling knowledge from a large deep teacher network to a much smaller student network for the task of road marking segmentation. In this work, we explore…
Feature Pyramid Grids
Kai Chen, Yuhang Cao, Chen Change Loy +2
Feature pyramid networks have been widely adopted in the object detection literature to improve feature representations for better handling of variations in scale. In this paper, w…
Self-Supervised Scene De-occlusion
Xiaohang Zhan, Xingang Pan, Bo Dai +3
Natural scene understanding is a challenging task, particularly when encountering images of multiple objects that are partially occluded. This obstacle is given rise by varying obj…