77 citations · 163 across the 16 of their papers we have counts for
16 papers
SSR: A Training-Free Approach for Streaming 3D Reconstruction
Hui Deng, Yuxin Mao, Yuxin He +1
Streaming 3D reconstruction demands long-horizon state updates under strict latency constraints, yet stateful recurrent models often suffer from geometric drift as errors accumulat…
Learning Spatial Decay for Vision Transformers
Yuxin Mao, Zhen Qin, Jinxing Zhou +4
Vision Transformers (ViTs) have revolutionized computer vision, yet their self-attention mechanism lacks explicit spatial inductive biases, leading to suboptimal performance on spa…
Label-anticipated Event Disentanglement for Audio-Visual Video Parsing
Jinxing Zhou, Dan Guo, Yuxin Mao +3
Audio-Visual Video Parsing (AVVP) task aims to detect and temporally locate events within audio and visual modalities. Multiple events can overlap in the timeline, making identific…
You Only Scan Once: Efficient Multi-dimension Sequential Modeling with LightNet
Zhen Qin, Yuxin Mao, Xuyang Shen +4
Linear attention mechanisms have gained prominence in causal language models due to their linear computational complexity and enhanced speed. However, the inherent decay mechanism…
TAVGBench: Benchmarking Text to Audible-Video Generation
Yuxin Mao, Xuyang Shen, Jing Zhang +5
The Text to Audible-Video Generation (TAVG) task involves generating videos with accompanying audio based on text descriptions. Achieving this requires skillful alignment of both a…
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…
RPEFlow: Multimodal Fusion of RGB-PointCloud-Event for Joint Optical Flow and Scene Flow Estimation
Zhexiong Wan, Yuxin Mao, Jing Zhang +1
Recently, the RGB images and point clouds fusion methods have been proposed to jointly estimate 2D optical flow and 3D scene flow. However, as both conventional RGB cameras and LiD…
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…
Contrastive Conditional Latent Diffusion for Audio-visual Segmentation
Yuxin Mao, Jing Zhang, Mochu Xiang +4
We propose a contrastive conditional latent diffusion model for audio-visual segmentation (AVS) to thoroughly investigate the impact of audio, where the correlation between audio a…
Mutual Information Regularization for Weakly-supervised RGB-D Salient Object Detection
Aixuan Li, Yuxin Mao, Jing Zhang +1
In this paper, we present a weakly-supervised RGB-D salient object detection model via scribble supervision. Specifically, as a multimodal learning task, we focus on effective mult…
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…
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…
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…
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…
PRAFlow_RVC: Pyramid Recurrent All-Pairs Field Transforms for Optical Flow Estimation in Robust Vision Challenge 2020
Zhexiong Wan, Yuxin Mao, Yuchao Dai
Optical flow estimation is an important computer vision task, which aims at estimating the dense correspondences between two frames. RAFT (Recurrent All Pairs Field Transforms) cur…