315 citations · 631 across the 22 of their papers we have counts for
8 papers · 1 filter
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…
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…
Mask-free OVIS: Open-Vocabulary Instance Segmentation without Manual Mask Annotations
Vibashan VS, Ning Yu, Chen Xing +5
Existing instance segmentation models learn task-specific information using manual mask annotations from base (training) categories. These mask annotations require tremendous human…
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…
HIVE: Harnessing Human Feedback for Instructional Visual Editing
Shu Zhang, Xinyi Yang, Yihao Feng +9
Incorporating human feedback has been shown to be crucial to align text generated by large language models to human preferences. We hypothesize that state-of-the-art instructional…
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…
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…