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A review of multimodal human activity recognition with special emphasis on classification, applications, challenges and future directions
Human activity recognition (HAR) is one of the most important and challenging problems in
the computer vision. It has critical application in wide variety of tasks including gaming …
the computer vision. It has critical application in wide variety of tasks including gaming …
Temporal action segmentation: An analysis of modern techniques
Temporal action segmentation (TAS) in videos aims at densely identifying video frames in
minutes-long videos with multiple action classes. As a long-range video understanding task …
minutes-long videos with multiple action classes. As a long-range video understanding task …
Moviechat: From dense token to sparse memory for long video understanding
Recently integrating video foundation models and large language models to build a video
understanding system can overcome the limitations of specific pre-defined vision tasks. Yet …
understanding system can overcome the limitations of specific pre-defined vision tasks. Yet …
Assembly101: A large-scale multi-view video dataset for understanding procedural activities
Assembly101 is a new procedural activity dataset featuring 4321 videos of people
assembling and disassembling 101" take-apart" toy vehicles. Participants work without fixed …
assembling and disassembling 101" take-apart" toy vehicles. Participants work without fixed …
Next-qa: Next phase of question-answering to explaining temporal actions
We introduce NExT-QA, a rigorously designed video question answering (VideoQA)
benchmark to advance video understanding from describing to explaining the temporal …
benchmark to advance video understanding from describing to explaining the temporal …
Anticipative video transformer
Abstract We propose Anticipative Video Transformer (AVT), an end-to-end attention-based
video modeling architecture that attends to the previously observed video in order to …
video modeling architecture that attends to the previously observed video in order to …
Diffusion action segmentation
Temporal action segmentation is crucial for understanding long-form videos. Previous works
on this task commonly adopt an iterative refinement paradigm by using multi-stage models …
on this task commonly adopt an iterative refinement paradigm by using multi-stage models …
Videollm: Modeling video sequence with large language models
With the exponential growth of video data, there is an urgent need for automated technology
to analyze and comprehend video content. However, existing video understanding models …
to analyze and comprehend video content. However, existing video understanding models …
A comprehensive study of deep video action recognition
Video action recognition is one of the representative tasks for video understanding. Over the
last decade, we have witnessed great advancements in video action recognition thanks to …
last decade, we have witnessed great advancements in video action recognition thanks to …
Longvlm: Efficient long video understanding via large language models
Abstract Empowered by Large Language Models (LLMs), recent advancements in Video-
based LLMs (VideoLLMs) have driven progress in various video understanding tasks. These …
based LLMs (VideoLLMs) have driven progress in various video understanding tasks. These …