35 citations · 147 across the 22 of their papers we have counts for
12 papers · 1 filter
BEV-DG: Cross-Modal Learning under Bird's-Eye View for Domain Generalization of 3D Semantic Segmentation
Miaoyu Li, Yachao Zhang, Xu MA +2
Cross-modal Unsupervised Domain Adaptation (UDA) aims to exploit the complementarity of 2D-3D data to overcome the lack of annotation in a new domain. However, UDA methods rely on…
Camouflaged Image Synthesis Is All You Need to Boost Camouflaged Detection
Haichao Zhang, Can Qin, Yu Yin +1
Camouflaged objects that blend into natural scenes pose significant challenges for deep-learning models to detect and synthesize. While camouflaged object detection is a crucial ta…
SnapFusion: Text-to-Image Diffusion Model on Mobile Devices within Two Seconds
Yanyu Li, Huan Wang, Qing Jin +6
Text-to-image diffusion models can create stunning images from natural language descriptions that rival the work of professional artists and photographers. However, these models ar…
UniControl: A Unified Diffusion Model for Controllable Visual Generation In the Wild
Can Qin, Shu Zhang, Ning Yu +10
Achieving machine autonomy and human control often represent divergent objectives in the design of interactive AI systems. Visual generative foundation models such as Stable Diffus…
Frame Flexible Network
Yitian Zhang, Yue Bai, Chang Liu +3
Existing video recognition algorithms always conduct different training pipelines for inputs with different frame numbers, which requires repetitive training operations and multipl…
Contrastive Alignment of Vision to Language Through Parameter-Efficient Transfer Learning
Zaid Khan, Yun Fu
Contrastive vision-language models (e.g. CLIP) are typically created by updating all the parameters of a vision model and language model through contrastive training. Can such mode…
Image as Set of Points
Xu Ma, Yuqian Zhou, Huan Wang +4
What is an image and how to extract latent features? Convolutional Networks (ConvNets) consider an image as organized pixels in a rectangular shape and extract features via convolu…
GlueGen: Plug and Play Multi-modal Encoders for X-to-image Generation
Can Qin, Ning Yu, Chen Xing +6
Text-to-image (T2I) models based on diffusion processes have achieved remarkable success in controllable image generation using user-provided captions. However, the tight coupling…
Iterative Soft Shrinkage Learning for Efficient Image Super-Resolution
Jiamian Wang, Huan Wang, Yulun Zhang +2
Image super-resolution (SR) has witnessed extensive neural network designs from CNN to transformer architectures. However, prevailing SR models suffer from prohibitive memory footp…
Why is the State of Neural Network Pruning so Confusing? On the Fairness, Comparison Setup, and Trainability in Network Pruning
Huan Wang, Can Qin, Yue Bai +1
The state of neural network pruning has been noticed to be unclear and even confusing for a while, largely due to "a lack of standardized benchmarks and metrics" [3]. To standardiz…
Unveiling the Unseen: A Comprehensive Survey on Explainable Anomaly Detection in Images and Videos
Yizhou Wang, Dongliang Guo, Sheng Li +2
Anomaly detection and localization in visual data, including images and videos, are crucial in machine learning and real-world applications. Despite rapid advancements in visual an…
Making Reconstruction-based Method Great Again for Video Anomaly Detection
Yizhou Wang, Can Qin, Yue Bai +3
Anomaly detection in videos is a significant yet challenging problem. Previous approaches based on deep neural networks employ either reconstruction-based or prediction-based appro…