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Found 17 papers, 6 papers with code
Towards Debiasing Frame Length Bias in Text-Video Retrieval via Causal Intervention
Many studies focus on improving pretraining or developing new backbones in text-video retrieval.
An Overview of Challenges in Egocentric Text-Video Retrieval
Text-video retrieval contains various challenges, including biases coming from diverse sources.
Is Bio-Inspired Learning Better than Backprop? Benchmarking Bio Learning vs. Backprop
Four of the five Bio-algorithms tested outperform BP by upto 5% accuracy when only 20% of the training dataset is available.
The Role of Robust Generalization in Continual Learning: Better Transfer and Less Forgetting
To the best of our knowledge, no existing technique can accomplish all of these objectives simultaneously.
Portmanteauing Features for Scene Text Recognition
To generate the portmanteau feature, a non-linear input pipeline with a block matrix initialization is presented.
Combined CNN Transformer Encoder for Enhanced Fine-grained Human Action Recognition
Fine-grained action recognition is a challenging task in computer vision.
Exploiting Semantic Role Contextualized Video Features for Multi-Instance Text-Video Retrieval EPIC-KITCHENS-100 Multi-Instance Retrieval Challenge 2022
In this report, we present our approach for EPIC-KITCHENS-100 Multi-Instance Retrieval Challenge 2022.
Ranked #9 on
Multi-Instance Retrieval
on EPIC-KITCHENS-100
Semantic Role Aware Correlation Transformer for Text to Video Retrieval
With the emergence of social media, voluminous video clips are uploaded every day, and retrieving the most relevant visual content with a language query becomes critical.
Ranked #13 on
Video Retrieval
on YouCook2
RoME: Role-aware Mixture-of-Expert Transformer for Text-to-Video Retrieval
Most methods consider only one joint embedding space between global visual and textual features without considering the local structures of each modality.
Ranked #12 on
Video Retrieval
on YouCook2
FashionSearchNet-v2: Learning Attribute Representations with Localization for Image Retrieval with Attribute Manipulation
A key challenge in e-commerce is that images have multiple attributes where users would like to manipulate and it is important to estimate discriminative feature representations for each of these attributes.
Joint Learning On The Hierarchy Representation for Fine-Grained Human Action Recognition
Inspired by the recently proposed hierarchy representation of fine-grained actions in FineGym and SlowFast network for action recognition, we propose a novel multi-task network which exploits the FineGym hierarchy representation to achieve effective joint learning and prediction for fine-grained human action recognition.
Prototype Recalls for Continual Learning
Without tampering with the performance on initial tasks, our method learns novel concepts given a few training examples of each class in new tasks.
Variational Prototype Replays for Continual Learning
In each classification task, our method learns a set of variational prototypes with their means and variances, where embedding of the samples from the same class can be represented in a prototypical distribution and class-representative prototypes are separated apart.
Egocentric Spatial Memory
Egocentric spatial memory (ESM) defines a memory system with encoding, storing, recognizing and recalling the spatial information about the environment from an egocentric perspective.
Learning Attribute Representations With Localization for Flexible Fashion Search
In this paper, we investigate ways of conducting a detailed fashion search using query images and attributes.
Egocentric Spatial Memory Network
During the exploration, our proposed ESM network model updates belief of the global map based on local observations using a recurrent neural network.
Deep Future Gaze: Gaze Anticipation on Egocentric Videos Using Adversarial Networks
Through competition with discriminator, the generator progressively improves quality of the future frames and thus anticipates future gaze better.
