research
∙
05/22/2023
BMB: Balanced Memory Bank for Imbalanced Semi-supervised Learning
Exploring a substantial amount of unlabeled data, semi-supervised learni...
share
research
∙
09/30/2022
Semi-Supervised Single-View 3D Reconstruction via Prototype Shape Priors
The performance of existing single-view 3D reconstruction methods heavil...
research
∙
11/30/2021
AdaViT: Adaptive Vision Transformers for Efficient Image Recognition
Built on top of self-attention mechanisms, vision transformers have demo...
research
∙
11/23/2021
Efficient Video Transformers with Spatial-Temporal Token Selection
Video transformers have achieved impressive results on major video recog...
research
∙
06/01/2021
Rethinking Pseudo Labels for Semi-Supervised Object Detection
Recent advances in semi-supervised object detection (SSOD) are largely d...
research
∙
04/20/2021
HMS: Hierarchical Modality Selection for Efficient Video Recognition
Videos are multimodal in nature. Conventional video recognition pipeline...
research
∙
12/29/2020
2D or not 2D? Adaptive 3D Convolution Selection for Efficient Video Recognition
3D convolutional networks are prevalent for video recognition. While ach...
research
∙
02/22/2020
Improving the Tightness of Convex Relaxation Bounds for Training Certifiably Robust Classifiers
Convex relaxations are effective for training and certifying neural netw...
research
∙
12/11/2019
Learning from Noisy Anchors for One-stage Object Detection
State-of-the-art object detectors rely on regressing and classifying an ...
research
∙
05/15/2019
Transferable Clean-Label Poisoning Attacks on Deep Neural Nets
In this paper, we explore clean-label poisoning attacks on deep convolut...
research
∙
04/11/2019
An Analysis of Pre-Training on Object Detection
We provide a detailed analysis of convolutional neural networks which ar...
research
∙
12/05/2017
R-FCN-3000 at 30fps: Decoupling Detection and Classification
We present R-FCN-3000, a large-scale real-time object detector in which ...
research
∙
11/03/2017
