arXiv AI
Jul 7
K9-Bench: Evaluating Multimodal LLMs on Canine-Centric Videos
arXiv:2607. 02680v1 Announce Type: cross Abstract: MLLMs have shown strong zero-shot capabilities across diverse inputs such as across images, video, audio, and text.
InterPet4D: A Multimodal 4D Human-Pet Interaction Dataset for Pet Motion Generation
Human-pet interaction estimation and generation remain underexplored due to the absence of a high-quality large-scale dataset. We present InterPet4D, the first multimodal dataset capturing natural interactions between humans and dogs.
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arXiv AI
1d ago
HiPHI: A Large-Scale Benchmark for High-Precision Human Motion and Object-Interaction
arXiv:2608. 16222v1 Announce Type: cross Abstract: Humanoid intelligence requires learning over an extremely diverse space of whole-body motions and physically grounded interactions.
arXiv Machine Learning
Jul 28
MIME: Multimodal Interactive Motion Encoder
arXiv:2607. 22702v1 Announce Type: cross Abstract: Text-motion representation learning has advanced rapidly, with growing interest in multi person interactions for animation, AR/VR, and embodied AI.
Hugging Face Trending Papers
Aug 5
Promptable Animal Pose Tracking Across Species
Animal pose estimation and tracking is important for wildlife monitoring and conservation research, and with limited expert time for labelling automated approaches are imperative. While human pose estimation and tracking has seen rapid progress thanks to large annotated datasets, animal pose remain challenging, due to large morphological and behavioural differences between species and limited annotated data.
arXiv AI
Jun 29
HAT-4D: Lifting Monocular Video for 4D Multi-Object Interactions via Human-Agent Collaboration
arXiv:2606. 28215v1 Announce Type: cross Abstract: Extracting dynamic 4D object interactions from massive, in-the-wild monocular videos offers a highly efficient data collection pathway for scaling Embodied AI and training VLAs.
arXiv Machine Learning
Jul 23
Agent-Centric Animal Pose Forecasting
arXiv:2607. 19548v1 Announce Type: new Abstract: Understanding animal behavior at an algorithmic level -- what animals attend to, how they form internal models and plans, and how this maps to action -- remains a central challenge in neuroscience and ethology.
arXiv AI
Jul 21
STAR: Skeletal Token Alignment and Rearrangement for Interaction Recognition
arXiv:2607. 17342v1 Announce Type: cross Abstract: Understanding physical human-robot and human-human interactions is a challenging yet emerging topic in 3D vision.
Hugging Face Trending Papers
Aug 5
Cooking beyond Frames: A Stereo Event Camera Dataset in the Kitchen
Event cameras, also known as neuromorphic cameras, have gained significant attention in recent years due to their high temporal resolution, high dynamic range, and low power consumption. While many studies and datasets in neuromorphic vision have focused on automotive and drone applications, human-centric daily-life scenarios remain largely underrepresented, despite their importance for developing and benchmarking event-based perception systems.
arXiv Machine Learning
Jun 18
Where Will They Go? Modelling Multimodal Pedestrian Manoeuvres from Ego-centric Videos
arXiv:2606. 18824v1 Announce Type: cross Abstract: Pedestrian trajectory prediction from an ego-centric camera is challenging since it depends on complex interactions with vehicles and scene context, as well as the intention of the pedestrian.
arXiv AI
6d ago
Towards Human Motion World Models via Executable Behaviour Representations
arXiv:2604. 18064v2 Announce Type: replace Abstract: Human motion world models should capture motion's intentionality by being executable: adaptable to different actions and capable of assessing motion quality.
arXiv AI
Jun 2
From Human Videos to Robot Manipulation: A Survey on Scalable Vision-Language-Action Learning with Human-Centric Data
arXiv:2606. 00054v1 Announce Type: cross Abstract: Recent progress in generalizable embodied control has been driven by large-scale pretraining of Vision-Language-Action (VLA) models.
arXiv AI
Aug 3
ActionParty: Multi-Subject Action Binding in Generative Video Games
arXiv:2604. 02330v2 Announce Type: replace-cross Abstract: Recent advances in video diffusion have enabled the development of "world models" capable of simulating interactive environments.