activity
20112022
most citedEnhancing Diversity in Teacher-Student Networks via Asymmetric branches for Unsupervised Person Re-identification

40 citations · 119 across the 12 of their papers we have counts for

collaborators

19 papers

cs.CV2022

THORN: Temporal Human-Object Relation Network for Action Recognition

Mohammed Guermal, Rui Dai, Francois Bremond

Most action recognition models treat human activities as unitary events. However, human activities often follow a certain hierarchy. In fact, many human activities are compositiona…

cs.CV20229 cited

Latent Image Animator: Learning to Animate Images via Latent Space Navigation

Yaohui Wang, Di Yang, Francois Bremond +1

Due to the remarkable progress of deep generative models, animating images has become increasingly efficient, whereas associated results have become increasingly realistic. Current…

cs.CV20225 cited

Unsupervised Lifelong Person Re-identification via Contrastive Rehearsal

Hao Chen, Benoit Lagadec, Francois Bremond

Existing unsupervised person re-identification (ReID) methods focus on adapting a model trained on a source domain to a fixed target domain. However, an adapted ReID model usually…

cs.CV2021

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…

cs.CV2021

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…

cs.CV202124 cited

UNIK: A Unified Framework for Real-world Skeleton-based Action Recognition

Di Yang, Yaohui Wang, Antitza Dantcheva +3

Action recognition based on skeleton data has recently witnessed increasing attention and progress. State-of-the-art approaches adopting Graph Convolutional networks (GCNs) can eff…