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- Generalized Intersection Over Union: A Metric and a Loss for Bounding Box Regression6,169
This paper introduces a generalized version of IoU ( GIoU) as a loss into the state-of-the art object detection frameworks, and shows a consistent improvement on their performance using both the standard, IoU based, and new, GIo U based, performance measures on popular object detection benchmarks.
- GMFlow: Learning Optical Flow via Global Matching583
A GMFlow framework is proposed, which consists of three main components: a customized Transformer for feature enhancement, a correlation and softmax layer for global feature matching, and a self-attention layer for flow propagation, which outperforms 31-refinements RAFT on the challenging Sintel benchmark, while using only one refinement and running faster.
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- Unifying Flow, Stereo and Depth Estimation433
It is demonstrated that cross-attention enables integration of knowledge from another image via cross-view interactions, which greatly improves the quality of the extracted features and enables cross-task transfer.
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- Embryo selection through artificial intelligence versus embryologists: a systematic review140
AI consistently outperformed the clinical teams in all the studies focused on embryo morphology and clinical outcome prediction during embryo selection assessment and predicted the likelihood of successful clinical pregnancy with greater accuracy than clinical embryologists, signifying greater reliability when compared to human prediction.
- JRMOT: A Real-Time 3D Multi-Object Tracker and a New Large-Scale Dataset113
JRMOT is a novel 3D MOT system that integrates information from RGB images and 3D point clouds to achieve real-time, state-of-the-art tracking performance and serves as first 3D tracking solution for the authors' benchmark.
- MARLIN: Masked Autoencoder for facial video Representation LearnINg109
The proposed framework, named MARLIN, is a facial video masked autoencoder that learns highly robust and generic facial embeddings from abundantly available non-annotated web crawled facial videos that can transfer across a variety of facial analysis tasks such as Facial Attribute Recognition (FAR), Facial Expression Recognition, DeepFake Detection, and Lip Synchronization.
- Attend and Discriminate105
This work proposes learning to exploit the latent relationships between multi-channel sensor modalities and specific activities, and incorporates a classification loss criterion to encourage minimal intra-class representation differences whilst maximising inter-class differences to achieve more discriminative features.
- Probabilistic Tracklet Scoring and Inpainting for Multiple Object Tracking99
A probabilistic autoregressive motion model is introduced to score tracklet proposals by directly measuring their likelihood, achieved by training the model to learn the underlying distribution of natural tracklets.
- Socially and Contextually Aware Human Motion and Pose Forecasting96
A novel framework to tackle both tasks of human motion (or trajectory) and body skeleton pose forecasting in a unified end-to-end pipeline is proposed and achieves a superior performance compared to several baselines on two social datasets.
- Online UAV Path Planning for Joint Detection and Tracking of Multiple Radio-Tagged Objects95
This paper derives a partially observable Markov decision process with a random finite set track-before-detect (TBD) multi-object filter, which also maintains a safe distance between the UAV and the objects of interest using a void probability constraint, and demonstrates the capability of the proposed approach to handle multiple radio-tagged objects subject to birth, death, and motion modes.
- Joint Learning of Social Groups, Individuals Action and Sub-group Activities in Videos90
This paper proposes an end-to-end trainable framework for the social task, and sets the state-of-the-art results on two widely adopted benchmarks for the traditional group activity recognition task.
- DrVideo: Document Retrieval Based Long Video Understanding89
DrVideo is proposed, a document-retrieval-based system designed for long video understanding that significantly outperforms existing LLM-based state-of-the-art methods on EgoSchema benchmark, MovieChat-1K benchmark, and the long split of Video-MME benchmark.
- TRiPOD: Human Trajectory and Pose Dynamics Forecasting in the Wild77
A novel TRajectory and POse Dynamics (nicknamed TRiPOD) method based on graph attentional networks to model the human-human and human-object interactions both in the input space and the output space (decoded future output).
- Looking Beyond Two Frames: End-to-End Multi-Object Tracking Using Spatial and Temporal Transformers74
MO3TR is presented: a truly end-to-end Transformer-based online multi-object tracking (MOT) framework that learns to handle occlusions, track initiation and termination without the need for an explicit data association module or any heuristics.
- JRDB-Act: A Large-scale Dataset for Spatio-temporal Action, Social Group and Activity Detection70
This paper introduces JRDB-Act, an extension of the existing JRDB, which is captured by a social mobile manipulator and reflects a real distribution of human daily-life actions in a university campus environment and develops an end-to-end trainable pipeline to learn and infer these tasks, i.e. individual action and social group detection.
- Distributed Multi-Object Tracking Under Limited Field of View Sensors65
A novel distributed multi-target algorithm is developed that fuses local multiobject states instead of local multi-object densities and uses a novel label consensus approach that reduces label inconsistency, caused by movements of objects from one node’s limited FoV to another.
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- ActiveRMAP: Radiance Field for Active Mapping And Planning53
This paper presents an RGB-only active vision framework using radiance field representation for active 3D reconstruction and planning in an online manner and suggests that the proposed method achieves competitive results compared to other offline methods and outperforms active reconstruction methods using NeRFs.
- JRDB-Pose: A Large-Scale Dataset for Multi-Person Pose Estimation and Tracking48
A thorough experimental study of state-of-the-art multi-person pose estimation and tracking methods on JRDB-Pose is conducted, showing that the dataset imposes new challenges for the existing methods.
- Deep Auto-Set46
This paper addresses HAR more naturally as a set prediction problem where the predictions are sets of ongoing activity elements with unfixed and unknown cardinality for the first time, and presents a novel HAR approach that learns to output activity sets using deep neural networks.
- Series2vec: similarity-based self-supervised representation learning for time series classification39
This work argues that time series analysis is fundamentally different in nature to either vision or natural language processing with respect to the forms of meaningful self-supervised learning tasks that can be defined, and introduces a novel approach called Series2Vec for self-supervised representation learning.
- Unsupervised Image Segmentation by Mutual Information Maximization and Adversarial Regularization39
This letter proposes a novel fully unsupervised semantic segmentation method, the so-called Information Maximization and Adversarial Regularization Segmentation (InMARS), Inspired by human perception which parses a scene into perceptual groups, rather than analyzing each pixel individually.
Publication data from OpenAlex, with missing venues and authors filled in from Crossref; citation counts are the higher of OpenAlex and Semantic Scholar, last synced 2026-10-14. One-sentence summaries under some papers are written by Semantic Scholar’s model. Citation counts may be lower than on Google Scholar, which indexes more sources.
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