Search Results for author:
Found 10 papers, 8 papers with code
DiP-GO: A Diffusion Pruner via Few-step Gradient Optimization
Finally, our method can identify an optimal SubNet through few-step gradient optimization and a simple post-processing procedure.
Hyper-YOLO: When Visual Object Detection Meets Hypergraph Computation
We introduce Hyper-YOLO, a new object detection method that integrates hypergraph computations to capture the complex high-order correlations among visual features.
Hand-Object Interaction Controller (HOIC): Deep Reinforcement Learning for Reconstructing Interactions with Physics
Hand manipulating objects is an important interaction motion in our daily activities.
Distribution-Aware Data Expansion with Diffusion Models
In this paper, we propose DistDiff, a training-free data expansion framework based on the distribution-aware diffusion model.
Relightable and Animatable Neural Avatars from Videos
To solve this ill-posed problem, we propose novel techniques to better model the geometry and shadow changes.
Focused and Collaborative Feedback Integration for Interactive Image Segmentation
Interactive image segmentation aims at obtaining a segmentation mask for an image using simple user annotations.
Physical Interaction: Reconstructing Hand-object Interactions with Physics
Single view-based reconstruction of hand-object interaction is challenging due to the severe observation missing caused by occlusions.
OcclusionFusion: Occlusion-aware Motion Estimation for Real-time Dynamic 3D Reconstruction
In our technique, the motion of visible regions is first estimated and combined with temporal information to infer the motion of the occluded regions through an LSTM-involved graph neural network.
Finding Optimal Tangent Points for Reducing Distortions of Hard-label Attacks
In this paper, we propose a novel geometric-based approach called Tangent Attack (TA), which identifies an optimal tangent point of a virtual hemisphere located on the decision boundary to reduce the distortion of the attack.
Simulating Unknown Target Models for Query-Efficient Black-box Attacks
The meta-gradients of this loss are then computed and accumulated from multiple tasks to update the Simulator and subsequently improve generalization.
