Search Results for author:
Found 5 papers, 2 papers with code
Learning to Complement and to Defer to Multiple Users
This process has three options: 1) AI autonomously classifies, 2) learning to complement, where AI collaborates with users, and 3) learning to defer, where AI defers to users.
Chaotic World: A Large and Challenging Benchmark for Human Behavior Understanding in Chaotic Events
Understanding and analyzing human behaviors (actions and interactions of people), voices, and sounds in chaotic events is crucial in many applications, e. g., crowd management, emergency response services.
Image-to-Video Generation via 3D Facial Dynamics
Video generation from a single face image is an interesting problem and usually tackled by utilizing Generative Adversarial Networks (GANs) to integrate information from the input face image and a sequence of sparse facial landmarks.
Joint Face Image Restoration and Frontalization for Recognition
First, MDFR is a well-designed encoder-decoder architecture which extracts feature representation from an input face image with arbitrary low-quality factors and restores it to a high-quality counterpart.
Single Image Super-Resolution via Residual Neuron Attention Networks
Experiments results demonstrate that our RNAN achieves the comparable results with state-of-the-art methods in terms of both quantitative metrics and visual quality, however, with simplified network architecture.
