77 citations · 284 across the 23 of their papers we have counts for
23 papers
MixRI: Mixing Features of Reference Images for Novel Object Pose Estimation
Xinhang Liu, Jiawei Shi, Zheng Dang +1
We present MixRI, a lightweight network that solves the CAD-based novel object pose estimation problem in RGB images. It can be instantly applied to a novel object at test time wit…
Multimodal Variational Auto-encoder based Audio-Visual Segmentation
Yuxin Mao, Jing Zhang, Mochu Xiang +2
We propose an Explicit Conditional Multimodal Variational Auto-Encoder (ECMVAE) for audio-visual segmentation (AVS), aiming to segment sound sources in the video sequence. Existing…
Decomposed Guided Dynamic Filters for Efficient RGB-Guided Depth Completion
Yufei Wang, Yuxin Mao, Qi Liu +1
RGB-guided depth completion aims at predicting dense depth maps from sparse depth measurements and corresponding RGB images, where how to effectively and efficiently exploit the mu…
Improving Audio-Visual Segmentation with Bidirectional Generation
Dawei Hao, Yuxin Mao, Bowen He +3
The aim of audio-visual segmentation (AVS) is to precisely differentiate audible objects within videos down to the pixel level. Traditional approaches often tackle this challenge b…
Linearized Relative Positional Encoding
Zhen Qin, Weixuan Sun, Kaiyue Lu +6
Relative positional encoding is widely used in vanilla and linear transformers to represent positional information. However, existing encoding methods of a vanilla transformer are…
Toeplitz Neural Network for Sequence Modeling
Zhen Qin, Xiaodong Han, Weixuan Sun +6
Sequence modeling has important applications in natural language processing and computer vision. Recently, the transformer-based models have shown strong performance on various seq…
A Revisit of the Normalized Eight-Point Algorithm and A Self-Supervised Deep Solution
Bin Fan, Yuchao Dai, Yongduek Seo +1
The normalized eight-point algorithm has been widely viewed as the cornerstone in two-view geometry computation, where the seminal Hartley's normalization has greatly improved the…
Learning Dense and Continuous Optical Flow from an Event Camera
Zhexiong Wan, Yuchao Dai, Yuxin Mao
Event cameras such as DAVIS can simultaneously output high temporal resolution events and low frame-rate intensity images, which own great potential in capturing scene motion, such…
Learning a Task-specific Descriptor for Robust Matching of 3D Point Clouds
Zhiyuan Zhang, Yuchao Dai, Bin Fan +2
Existing learning-based point feature descriptors are usually task-agnostic, which pursue describing the individual 3D point clouds as accurate as possible. However, the matching t…
CU-Net: LiDAR Depth-Only Completion With Coupled U-Net
Yufei Wang, Yuchao Dai, Qi Liu +3
LiDAR depth-only completion is a challenging task to estimate dense depth maps only from sparse measurement points obtained by LiDAR. Even though the depth-only methods have been w…
Searching Dense Point Correspondences via Permutation Matrix Learning
Zhiyuan Zhang, Jiadai Sun, Yuchao Dai +2
Although 3D point cloud data has received widespread attentions as a general form of 3D signal expression, applying point clouds to the task of dense correspondence estimation betw…
Deep Idempotent Network for Efficient Single Image Blind Deblurring
Yuxin Mao, Zhexiong Wan, Yuchao Dai +1
Single image blind deblurring is highly ill-posed as neither the latent sharp image nor the blur kernel is known. Even though considerable progress has been made, several major dif…
VRNet: Learning the Rectified Virtual Corresponding Points for 3D Point Cloud Registration
Zhiyuan Zhang, Jiadai Sun, Yuchao Dai +2
3D point cloud registration is fragile to outliers, which are labeled as the points without corresponding points. To handle this problem, a widely adopted strategy is to estimate t…
MUNet: Motion Uncertainty-aware Semi-supervised Video Object Segmentation
Jiadai Sun, Yuxin Mao, Yuchao Dai +2
The task of semi-supervised video object segmentation (VOS) has been greatly advanced and state-of-the-art performance has been made by dense matching-based methods. The recent met…
Dense Uncertainty Estimation via an Ensemble-based Conditional Latent Variable Model
Jing Zhang, Yuchao Dai, Mehrtash Harandi +3
Uncertainty estimation has been extensively studied in recent literature, which can usually be classified as aleatoric uncertainty and epistemic uncertainty. In current aleatoric u…
A General Divergence Modeling Strategy for Salient Object Detection
Xinyu Tian, Jing Zhang, Yuchao Dai
Salient object detection is subjective in nature, which implies that multiple estimations should be related to the same input image. Most existing salient object detection models a…
Dense Uncertainty Estimation
Jing Zhang, Yuchao Dai, Mochu Xiang +7
Deep neural networks can be roughly divided into deterministic neural networks and stochastic neural networks.The former is usually trained to achieve a mapping from input space to…
End-to-end Learning the Partial Permutation Matrix for Robust 3D Point Cloud Registration
Zhiyuan Zhang, Jiadai Sun, Yuchao Dai +3
Even though considerable progress has been made in deep learning-based 3D point cloud processing, how to obtain accurate correspondences for robust registration remains a major cha…
RGB-D Saliency Detection via Cascaded Mutual Information Minimization
Jing Zhang, Deng-Ping Fan, Yuchao Dai +4
Existing RGB-D saliency detection models do not explicitly encourage RGB and depth to achieve effective multi-modal learning. In this paper, we introduce a novel multi-stage cascad…
PR-RRN: Pairwise-Regularized Residual-Recursive Networks for Non-rigid Structure-from-Motion
Haitian Zeng, Yuchao Dai, Xin Yu +2
We propose PR-RRN, a novel neural-network based method for Non-rigid Structure-from-Motion (NRSfM). PR-RRN consists of Residual-Recursive Networks (RRN) and two extra regularizatio…
SUNet: Symmetric Undistortion Network for Rolling Shutter Correction
Bin Fan, Yuchao Dai, Mingyi He
The vast majority of modern consumer-grade cameras employ a rolling shutter mechanism, leading to image distortions if the camera moves during image acquisition. In this paper, we…
Complementary Patch for Weakly Supervised Semantic Segmentation
Fei Zhang, Chaochen Gu, Chenyue Zhang +1
Weakly Supervised Semantic Segmentation (WSSS) based on image-level labels has been greatly advanced by exploiting the outputs of Class Activation Map (CAM) to generate the pseudo…
Generative Transformer for Accurate and Reliable Salient Object Detection
Yuxin Mao, Jing Zhang, Zhexiong Wan +6
Transformer, which originates from machine translation, is particularly powerful at modeling long-range dependencies. Currently, the transformer is making revolutionary progress in…