arXiv Computer Vision
Occluded Gait Recognition with Mixture of Experts: An Action Detection Perspective
Read the original on arXiv Computer Vision →The Flow has not summarised this story yet — read it at arXiv Computer Vision.
Related stories
arXiv Computer Vision
Sep 11
MMGait: Benchmarking and Unifying Gait Recognition across Heterogeneous Modalities
MMGait is a large‑scale multi‑sensor benchmark that aligns visible, infrared, depth, LiDAR, and radar observations at the sequence level, enabling evaluation of single‑modal, cross‑modal, and multi‑modal gait recognition. The study shows that modality rankings shift with probe conditions, cross‑modal alignment remains challenging, and fusion can yield complementary gains. To address the scalability issue of training separate experts, the authors propose Omni‑Modal Gait Recognition and its implementation, OmniGait++, which unifies all recognition settings within a shared identity space using modality‑specific front ends, a shared encoder, and an anchor‑guided fusion module. whyItMatters":"MMGait provides a common testbed for heterogeneous gait sensing and demonstrates that unified recognition across varying modality availability is feasible, offering a scalable alternative to task‑specific experts."
Hugging Face Trending Papers
Jul 22
MoAKE: Toward Unified All-in-One Action Quality Assessment via Mixture of Action Knowledge Experts
Action Quality Assessment (AQA) aims to objectively evaluate performance quality from action videos. Most existing methods follow a ``one-by-one'' paradigm, training a separate model for each action type.
arXiv AI
Jul 14
On Occlusions in Video Action Detection: Benchmark Datasets And Training Recipes
arXiv:2410. 19553v2 Announce Type: replace-cross Abstract: This paper explores the impact of occlusions in video action detection.
arXiv AI
Jul 1
SkillSpotter: Pose-Aware Multi-View Skilled Action Detection and Grading in Ego-Exo Videos
arXiv:2606. 31127v1 Announce Type: cross Abstract: To enable personalized, real-time coaching using Augmented Reality glasses or fixed camera setups in domains such as sports, cooking, or music, a system must understand not just what a person does, but how well they execute an activity.
arXiv Computer Vision
Aug 28
Who Remains, What Changes: Identity Anchored Composed Gait Retrieval
The paper introduces Composed Gait Retrieval (CoGR), a task that retrieves a target gait sequence using a reference sequence and a natural language modification query. To support this, the authors create the first gait-language datasets—Language‑Augmented CCPG and Language‑Augmented CASIA‑B—via an automated annotation pipeline powered by large vision‑language models. They propose ComposeGait, an identity‑anchored composition framework with a Part‑aware Identity Adapter that injects identity tokens into a shared Q‑Former, achieving state‑of‑the‑art retrieval performance on both benchmarks.
arXiv Computer Vision
1d ago
Vocabulary-Guided Gait Recognition
arXiv:2609.18413v1 Announce Type: new Abstract: What is a gait? Appearance-based gait networks consider a gait as the human shape and motion information from images. Model-based gait networks treat a...