research
∙
06/07/2023
Contrastive Lift: 3D Object Instance Segmentation by Slow-Fast Contrastive Fusion
Instance segmentation in 3D is a challenging task due to the lack of lar...
share
research
∙
03/17/2023
Refinement for Absolute Pose Regression with Neural Feature Synthesis
Absolute Pose Regression (APR) methods use deep neural networks to direc...
research
∙
11/28/2022
A Light Touch Approach to Teaching Transformers Multi-view Geometry
Transformers are powerful visual learners, in large part due to their co...
research
∙
03/22/2022
A Prompt Array Keeps the Bias Away: Debiasing Vision-Language Models with Adversarial Learning
Vision-language models can encode societal biases and stereotypes, but t...
research
∙
11/11/2021
Dynamic Iterative Refinement for Efficient 3D Hand Pose Estimation
While hand pose estimation is a critical component of most interactive e...
research
∙
05/02/2021
Data-driven Weight Initialization with Sylvester Solvers
In this work, we propose a data-driven scheme to initialize the paramete...
research
∙
08/06/2020
Structured Convolutions for Efficient Neural Network Design
In this work, we tackle model efficiency by exploiting redundancy in the...
research
∙
04/20/2020
LSQ+: Improving low-bit quantization through learnable offsets and better initialization
Unlike ReLU, newer activation functions (like Swish, H-swish, Mish) that...
research
∙
02/28/2020
Learned Threshold Pruning
This paper presents a novel differentiable method for unstructured weigh...
research
∙
11/28/2019
QKD: Quantization-aware Knowledge Distillation
Quantization and Knowledge distillation (KD) methods are widely used to ...
research
∙
09/25/2019
Teacher-Student Learning Paradigm for Tri-training: An Efficient Method for Unlabeled Data Exploitation
Given that labeled data is expensive to obtain in real-world scenarios, ...
research
∙
12/29/2018
Annotation-cost Minimization for Medical Image Segmentation using Suggestive Mixed Supervision Fully Convolutional Networks
For medical image segmentation, most fully convolutional networks (FCNs)...
research
∙
09/29/2018
FusedLSTM: Fusing frame-level and video-level features for Content-based Video Relevance Prediction
This paper describes two of my best performing approaches on the Content...
research
∙
09/16/2016