Search Results for author:
Found 10 papers, 4 papers with code
Hand-Transformer: Non-Autoregressive Structured Modeling for 3D Hand Pose Estimation
To address this issue, we connect this structured output learning problem with the structured modeling framework in sequence transduction field.
TNASP: A Transformer-based NAS Predictor with a Self-evolution Framework
Predictor-based Neural Architecture Search (NAS) continues to be an important topic because it aims to mitigate the time-consuming search procedure of traditional NAS methods.
GDP: Stabilized Neural Network Pruning via Gates with Differentiable Polarization
During the training process, the polarization effect will drive a subset of gates to smoothly decrease to exact zero, while other gates gradually stay away from zero by a large margin.
Hand Image Understanding via Deep Multi-Task Learning
To further improve the performance of these tasks, we propose a novel Hand Image Understanding (HIU) framework to extract comprehensive information of the hand object from a single RGB image, by jointly considering the relationships between these tasks.
UMEC: Unified model and embedding compression for efficient recommendation systems
The recommendation system (RS) plays an important role in the content recommendation and retrieval scenarios.
Fashion Captioning: Towards Generating Accurate Descriptions with Semantic Rewards
The goal of this work is to develop a novel learning framework for accurate and expressive fashion captioning.
ResRep: Lossless CNN Pruning via Decoupling Remembering and Forgetting
Via training with regular SGD on the former but a novel update rule with penalty gradients on the latter, we realize structured sparsity.
Learning Color Compatibility in Fashion Outfits
Color compatibility is important for evaluating the compatibility of a fashion outfit, yet it was neglected in previous studies.
DCNAS: Densely Connected Neural Architecture Search for Semantic Image Segmentation
Neural Architecture Search (NAS) has shown great potentials in automatically designing scalable network architectures for dense image predictions.
Ranked #6 on
Semantic Segmentation
on Cityscapes test
