200 citations · 549 across the 29 of their papers we have counts for
10 papers · 1 filter
Task2Sim : Towards Effective Pre-training and Transfer from Synthetic Data
Samarth Mishra, Rameswar Panda, Cheng Perng Phoo +5
Pre-training models on Imagenet or other massive datasets of real images has led to major advances in computer vision, albeit accompanied with shortcomings related to curation cost…
Dynamic Network Quantization for Efficient Video Inference
Ximeng Sun, Rameswar Panda, Chun-Fu Chen +3
Deep convolutional networks have recently achieved great success in video recognition, yet their practical realization remains a challenge due to the large amount of computational…
Can An Image Classifier Suffice For Action Recognition?
Quanfu Fan, Chun-Fu, Chen +1
We explore a new perspective on video understanding by casting the video recognition problem as an image recognition task. Our approach rearranges input video frames into super ima…
Dynamic Distillation Network for Cross-Domain Few-Shot Recognition with Unlabeled Data
Ashraful Islam, Chun-Fu Chen, Rameswar Panda +3
Most existing works in few-shot learning rely on meta-learning the network on a large base dataset which is typically from the same domain as the target dataset. We tackle the prob…
RegionViT: Regional-to-Local Attention for Vision Transformers
Chun-Fu Chen, Rameswar Panda, Quanfu Fan
Vision transformer (ViT) has recently shown its strong capability in achieving comparable results to convolutional neural networks (CNNs) on image classification. However, vanilla…
AdaMML: Adaptive Multi-Modal Learning for Efficient Video Recognition
Rameswar Panda, Chun-Fu Chen, Quanfu Fan +4
Multi-modal learning, which focuses on utilizing various modalities to improve the performance of a model, is widely used in video recognition. While traditional multi-modal learni…
Detector-Free Weakly Supervised Grounding by Separation
Assaf Arbelle, Sivan Doveh, Amit Alfassy +14
Nowadays, there is an abundance of data involving images and surrounding free-form text weakly corresponding to those images. Weakly Supervised phrase-Grounding (WSG) deals with th…
CrossViT: Cross-Attention Multi-Scale Vision Transformer for Image Classification
Chun-Fu Chen, Quanfu Fan, Rameswar Panda
The recently developed vision transformer (ViT) has achieved promising results on image classification compared to convolutional neural networks. Inspired by this, in this paper, w…
A Broad Study on the Transferability of Visual Representations with Contrastive Learning
Ashraful Islam, Chun-Fu Chen, Rameswar Panda +3
Tremendous progress has been made in visual representation learning, notably with the recent success of self-supervised contrastive learning methods. Supervised contrastive learnin…
Improved Techniques for Quantizing Deep Networks with Adaptive Bit-Widths
Ximeng Sun, Rameswar Panda, Chun-Fu Chen +6
Quantizing deep networks with adaptive bit-widths is a promising technique for efficient inference across many devices and resource constraints. In contrast to static methods that…