Search Results for author:
Found 4 papers, 3 papers with code
Deep Transferring Quantization
Specifically, we propose a method named deep transferring quantization (DTQ) to effectively exploit the knowledge in a pre-trained full-precision model.
Towards Stable Test-Time Adaptation in Dynamic Wild World
In this paper, we investigate the unstable reasons and find that the batch norm layer is a crucial factor hindering TTA stability.
Debiased Visual Question Answering from Feature and Sample Perspectives
From the sample perspective, we construct two types of negative samples to assist the training of the models, without introducing additional annotations.
Modular Graph Attention Network for Complex Visual Relational Reasoning
Moreover, to capture the complex logic in a query, we construct a relational graph to represent the visual objects and their relationships, and propose a multi-step reasoning method to progressively understand the complex logic.
Ranked #2 on
Referring Expression Comprehension
on CLEVR-Ref+
