67 citations · 127 across the 17 of their papers we have counts for
8 papers · 1 filter
Adaptive Label Smoothing with Self-Knowledge in Natural Language Generation
Dongkyu Lee, Ka Chun Cheung, Nevin L. Zhang
Overconfidence has been shown to impair generalization and calibration of a neural network. Previous studies remedy this issue by adding a regularization term to a loss function, p…
Hard Gate Knowledge Distillation -- Leverage Calibration for Robust and Reliable Language Model
Dongkyu Lee, Zhiliang Tian, Yingxiu Zhao +2
In knowledge distillation, a student model is trained with supervisions from both knowledge from a teacher and observations drawn from a training data distribution. Knowledge of a…
NeuralMarker: A Framework for Learning General Marker Correspondence
Zhaoyang Huang, Xiaokun Pan, Weihong Pan +5
We tackle the problem of estimating correspondences from a general marker, such as a movie poster, to an image that captures such a marker. Conventionally, this problem is addresse…
Learning Degradation Representations for Image Deblurring
Dasong Li, Yi Zhang, Ka Chun Cheung +3
In various learning-based image restoration tasks, such as image denoising and image super-resolution, the degradation representations were widely used to model the degradation pro…
NVIDIA-UNIBZ Submission for EPIC-KITCHENS-100 Action Anticipation Challenge 2022
Tsung-Ming Tai, Oswald Lanz, Giuseppe Fiameni +5
In this report, we describe the technical details of our submission for the EPIC-Kitchen-100 action anticipation challenge. Our modelings, the higher-order recurrent space-time tra…
A Simple Baseline for Video Restoration with Grouped Spatial-temporal Shift
Dasong Li, Xiaoyu Shi, Yi Zhang +5
Video restoration, which aims to restore clear frames from degraded videos, has numerous important applications. The key to video restoration depends on utilizing inter-frame infor…
MPPNet: Multi-Frame Feature Intertwining with Proxy Points for 3D Temporal Object Detection
Xuesong Chen, Shaoshuai Shi, Benjin Zhu +3
Accurate and reliable 3D detection is vital for many applications including autonomous driving vehicles and service robots. In this paper, we present a flexible and high-performanc…
FlowFormer: A Transformer Architecture for Optical Flow
Zhaoyang Huang, Xiaoyu Shi, Chao Zhang +5
We introduce optical Flow transFormer, dubbed as FlowFormer, a transformer-based neural network architecture for learning optical flow. FlowFormer tokenizes the 4D cost volume buil…