Rlipv2: Fast scaling of relational language-image pre-training
Abstract Relational Language-Image Pre-training (RLIP) aims to align vision representations
with relational texts, thereby advancing the capability of relational reasoning in computer …
with relational texts, thereby advancing the capability of relational reasoning in computer …
Re-mine, learn and reason: Exploring the cross-modal semantic correlations for language-guided hoi detection
Abstract Human-Object Interaction (HOI) detection is a challenging computer vision task that
requires visual models to address the complex interactive relationship between humans and …
requires visual models to address the complex interactive relationship between humans and …
From detection to understanding: A survey on representation learning for human-object interaction
T Luo, S Guan, R Yang, J Smith - Neurocomputing, 2023 - Elsevier
Abstract Human-Object Interaction (HOI) detection is a critical topic in the visual
understanding field. With the development of deep learning models, the research of HOI …
understanding field. With the development of deep learning models, the research of HOI …
Mining cross-person cues for body-part interactiveness learning in hoi detection
Abstract Human-Object Interaction (HOI) detection plays a crucial role in activity
understanding. Though significant progress has been made, interactiveness learning …
understanding. Though significant progress has been made, interactiveness learning …
Viplo: Vision transformer based pose-conditioned self-loop graph for human-object interaction detection
J Park, JW Park, JS Lee - … of the IEEE/CVF Conference on …, 2023 - openaccess.thecvf.com
Abstract Human-Object Interaction (HOI) detection, which localizes and infers relationships
between human and objects, plays an important role in scene understanding. Although two …
between human and objects, plays an important role in scene understanding. Although two …
Agglomerative transformer for human-object interaction detection
We propose an agglomerative Transformer (AGER) that enables Transformer-based human-
object interaction (HOI) detectors to flexibly exploit extra instance-level cues in a single …
object interaction (HOI) detectors to flexibly exploit extra instance-level cues in a single …
Category query learning for human-object interaction classification
Unlike most previous HOI methods that focus on learning better human-object features, we
propose a novel and complementary approach called category query learning. Such queries …
propose a novel and complementary approach called category query learning. Such queries …
Unified visual relationship detection with vision and language models
This work focuses on training a single visual relationship detector predicting over the union
of label spaces from multiple datasets. Merging labels spanning different datasets could be …
of label spaces from multiple datasets. Merging labels spanning different datasets could be …
Detecting any human-object interaction relationship: Universal hoi detector with spatial prompt learning on foundation models
Human-object interaction (HOI) detection aims to comprehend the intricate relationships
between humans and objects, predicting triplets, and serving as the foundation for …
between humans and objects, predicting triplets, and serving as the foundation for …
Neural-logic human-object interaction detection
The interaction decoder utilized in prevalent Transformer-based HOI detectors typically
accepts pre-composed human-object pairs as inputs. Though achieving remarkable …
accepts pre-composed human-object pairs as inputs. Though achieving remarkable …