2 citations · 4 across the 7 of their papers we have counts for
9 papers
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…
Autoregressive Image Generation with Linear Complexity: A Spatial-Aware Decay Perspective
Yuxin Mao, Zhen Qin, Jinxing Zhou +6
Autoregressive (AR) models have garnered significant attention in image generation for their ability to effectively capture both local and global structures within visual data. How…
SABER: Spatially Consistent 3D Universal Adversarial Objects for BEV Detectors
Aixuan Li, Mochu Xiang, Bosen Hou +3
Adversarial robustness of BEV 3D object detectors is critical for autonomous driving (AD). Existing invasive attacks require altering the target vehicle itself (e.g. attaching patc…
A Generative Victim Model for Segmentation
Aixuan Li, Jing Zhang, Jiawei Shi +2
We find that the well-trained victim models (VMs), against which the attacks are generated, serve as fundamental prerequisites for adversarial attacks, i.e. a segmentation VM is ne…
Generative Edge Detection with Stable Diffusion
Caixia Zhou, Yaping Huang, Mochu Xiang +3
Edge detection is typically viewed as a pixel-level classification problem mainly addressed by discriminative methods. Recently, generative edge detection methods, especially diffu…
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…