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Found 15 papers, 7 papers with code
Mind the Gap in Distilling StyleGANs
To further enhance the semantic consistency between the teacher and student model, we present a latent-direction-based distillation loss that preserves the semantic relations in latent space.
A Comprehensive Overhaul of Distilling Unconditional GANs
To further enhance the semantic consistency between the teacher and student model, we present another latent-direction-based distillation loss that preserves the semantic relations in latent space.
Towards Evaluating and Training Verifiably Robust Neural Networks
Recent works have shown that interval bound propagation (IBP) can be used to train verifiably robust neural networks.
X-view: Non-egocentric Multi-View 3D Object Detector
3D object detection algorithms for autonomous driving reason about 3D obstacles either from 3D birds-eye view or perspective view or both.
Suppress-and-Refine Framework for End-to-End 3D Object Detection
In this work, we propose a suppress-and-refine framework to remove these handcrafted components.
Computation-Efficient Knowledge Distillation via Uncertainty-Aware Mixup
Our goal is to achieve a performance comparable to conventional knowledge distillation with a lower computation cost during training.
Knowledge Distillation Meets Self-Supervision
Knowledge distillation, which involves extracting the "dark knowledge" from a teacher network to guide the learning of a student network, has emerged as an important technique for model compression and transfer learning.
Ranked #32 on
Knowledge Distillation
on ImageNet
A Local-to-Global Approach to Multi-modal Movie Scene Segmentation
Scene, as the crucial unit of storytelling in movies, contains complex activities of actors and their interactions in a physical environment.
Boundary-Aware Dense Feature Indicator for Single-Stage 3D Object Detection from Point Clouds
3D object detection based on point clouds has become more and more popular.
PI-RCNN: An Efficient Multi-sensor 3D Object Detector with Point-based Attentive Cont-conv Fusion Module
Moreover, based on the PACF module, we propose a 3D multi-sensor multi-task network called Pointcloud-Image RCNN(PI-RCNN as brief), which handles the image segmentation and 3D object detection tasks.
Learning with Social Influence through Interior Policy Differentiation
In this work we model the social influence into the scheme of reinforcement learning, enabling the agents to learn both from the environment and from their peers.
Training-Time-Friendly Network for Real-Time Object Detection
Experiments on MS COCO show that our TTFNet has great advantages in balancing training time, inference speed, and accuracy.
Removing out-of-focus blur from a single image
Reproducing an all-in-focus image from an image with defocus regions is of practical value in many applications, eg, digital photography, and robotics.
Weighted total variation based convex clustering
Data clustering is a fundamental problem with a wide range of applications.
Estimating Defocus Blur via Rank of Local Patches
This paper addresses the problem of defocus map estimation from a single image.
