9 citations · 40 across the 13 of their papers we have counts for
17 papers
AAN: Attributes-Aware Network for Temporal Action Detection
Rui Dai, Srijan Das, Michael S. Ryoo +1
The challenge of long-term video understanding remains constrained by the efficient extraction of object semantics and the modelling of their relationships for downstream tasks. Al…
Attending Generalizability in Course of Deep Fake Detection by Exploring Multi-task Learning
Pranav Balaji, Abhijit Das, Srijan Das +1
This work explores various ways of exploring multi-task learning (MTL) techniques aimed at classifying videos as original or manipulated in cross-manipulation scenario to attend ge…
Seeing the Pose in the Pixels: Learning Pose-Aware Representations in Vision Transformers
Dominick Reilly, Aman Chadha, Srijan Das
Human perception of surroundings is often guided by the various poses present within the environment. Many computer vision tasks, such as human action recognition and robot imitati…
Video + CLIP Baseline for Ego4D Long-term Action Anticipation
Srijan Das, Michael S. Ryoo
In this report, we introduce our adaptation of image-text models for long-term action anticipation. Our Video + CLIP framework makes use of a large-scale pre-trained paired image-t…
Learning Viewpoint-Agnostic Visual Representations by Recovering Tokens in 3D Space
Jinghuan Shang, Srijan Das, Michael S. Ryoo
Humans are remarkably flexible in understanding viewpoint changes due to visual cortex supporting the perception of 3D structure. In contrast, most of the computer vision models th…
Does Self-supervised Learning Really Improve Reinforcement Learning from Pixels?
Xiang Li, Jinghuan Shang, Srijan Das +1
We investigate whether self-supervised learning (SSL) can improve online reinforcement learning (RL) from pixels. We extend the contrastive reinforcement learning framework (e.g.,…
CD-Net: Histopathology Representation Learning using Pyramidal Context-Detail Network
Saarthak Kapse, Srijan Das, Prateek Prasanna
Extracting rich phenotype information, such as cell density and arrangement, from whole slide histology images (WSIs), requires analysis of large field of view, i.e more contexual…
ViewCLR: Learning Self-supervised Video Representation for Unseen Viewpoints
Srijan Das, Michael S. Ryoo
Learning self-supervised video representation predominantly focuses on discriminating instances generated from simple data augmentation schemes. However, the learned representation…
Cross-modal Manifold Cutmix for Self-supervised Video Representation Learning
Srijan Das, Michael S. Ryoo
Contrastive representation learning of videos highly relies on the availability of millions of unlabelled videos. This is practical for videos available on web but acquiring such l…
MS-TCT: Multi-Scale Temporal ConvTransformer for Action Detection
Rui Dai, Srijan Das, Kumara Kahatapitiya +2
Action detection is an essential and challenging task, especially for densely labelled datasets of untrimmed videos. The temporal relation is complex in those datasets, including c…
CTRN: Class-Temporal Relational Network for Action Detection
Rui Dai, Srijan Das, Francois Bremond
Action detection is an essential and challenging task, especially for densely labelled datasets of untrimmed videos. There are many real-world challenges in those datasets, such as…
Weakly-supervised Joint Anomaly Detection and Classification
Snehashis Majhi, Srijan Das, Francois Bremond +2
Anomaly activities such as robbery, explosion, accidents, etc. need immediate actions for preventing loss of human life and property in real world surveillance systems. Although th…
Learning an Augmented RGB Representation with Cross-Modal Knowledge Distillation for Action Detection
Rui Dai, Srijan Das, Francois Bremond
In video understanding, most cross-modal knowledge distillation (KD) methods are tailored for classification tasks, focusing on the discriminative representation of the trimmed vid…
VPN++: Rethinking Video-Pose embeddings for understanding Activities of Daily Living
Srijan Das, Rui Dai, Di Yang +1
Many attempts have been made towards combining RGB and 3D poses for the recognition of Activities of Daily Living (ADL). ADL may look very similar and often necessitate to model fi…
Toyota Smarthome Untrimmed: Real-World Untrimmed Videos for Activity Detection
Rui Dai, Srijan Das, Saurav Sharma +4
Designing activity detection systems that can be successfully deployed in daily-living environments requires datasets that pose the challenges typical of real-world scenarios. In t…
VPN: Learning Video-Pose Embedding for Activities of Daily Living
Srijan Das, Saurav Sharma, Rui Dai +2
In this paper, we focus on the spatio-temporal aspect of recognizing Activities of Daily Living (ADL). ADL have two specific properties (i) subtle spatio-temporal patterns and (ii)…
Deep-Temporal LSTM for Daily Living Action Recognition
Srijan Das, Michal Koperski, Francois Bremond +1
In this paper, we propose to improve the traditional use of RNNs by employing a many to many model for video classification. We analyze the importance of modeling spatial layout an…