2 citations · 3 across the 7 of their papers we have counts for
7 papers
Motion-Adaptive Temporal Attention for Lightweight Video Generation with Stable Diffusion
Rui Hong, Shuxue Quan
We present a motion-adaptive temporal attention mechanism for parameter-efficient video generation built upon frozen Stable Diffusion models. Rather than treating all video content…
To See or To Please: Uncovering Visual Sycophancy and Split Beliefs in VLMs
Rui Hong, Shuxue Quan
When VLMs answer correctly, do they genuinely rely on visual information? We introduce a Tri-Layer Diagnostic Framework with three per-sample metrics: Latent Anomaly Detection, Vis…
Vision Backbone Enhancement via Multi-Stage Cross-Scale Attention
Liang Shang, Yanli Liu, Zhengyang Lou +4
Convolutional neural networks (CNNs) and vision transformers (ViTs) have achieved remarkable success in various vision tasks. However, many architectures do not consider interactio…
SMOF: Squeezing More Out of Filters Yields Hardware-Friendly CNN Pruning
Yanli Liu, Bochen Guan, Qinwen Xu +2
For many years, the family of convolutional neural networks (CNNs) has been a workhorse in deep learning. Recently, many novel CNN structures have been designed to address increasi…
RobustFusion: Robust Volumetric Performance Reconstruction under Human-object Interactions from Monocular RGBD Stream
Zhuo Su, Lan Xu, Dawei Zhong +4
High-quality 4D reconstruction of human performance with complex interactions to various objects is essential in real-world scenarios, which enables numerous immersive VR/AR applic…
PoP-Net: Pose over Parts Network for Multi-Person 3D Pose Estimation from a Depth Image
Yuliang Guo, Zhong Li, Zekun Li +3
In this paper, a real-time method called PoP-Net is proposed to predict multi-person 3D poses from a depth image. PoP-Net learns to predict bottom-up part representations and top-d…
Object Detection in the Context of Mobile Augmented Reality
Xiang Li, Yuan Tian, Fuyao Zhang +2
In the past few years, numerous Deep Neural Network (DNN) models and frameworks have been developed to tackle the problem of real-time object detection from RGB images. Ordinary ob…