Video understanding with large language models: A survey
With the burgeoning growth of online video platforms and the escalating volume of video
content, the demand for proficient video understanding tools has intensified markedly. Given …
content, the demand for proficient video understanding tools has intensified markedly. Given …
Finematch: Aspect-based fine-grained image and text mismatch detection and correction
Recent progress in large-scale pre-training has led to the development of advanced vision-
language models (VLMs) with remarkable proficiency in comprehending and generating …
language models (VLMs) with remarkable proficiency in comprehending and generating …
EAGLE: Egocentric AGgregated Language-video Engine
The rapid evolution of egocentric video analysis brings new insights into understanding
human activities and intentions from a first-person perspective. Despite this progress, the …
human activities and intentions from a first-person perspective. Despite this progress, the …
Cardiff: Video salient object ranking chain of thought reasoning for saliency prediction with diffusion
Video saliency prediction aims to identify the regions in a video that attract human attention
and gaze, driven by bottom-up features from the video and top-down processes like memory …
and gaze, driven by bottom-up features from the video and top-down processes like memory …
Trace: Temporal grounding video llm via causal event modeling
Video Temporal Grounding (VTG) is a crucial capability for video understanding models and
plays a vital role in downstream tasks such as video browsing and editing. To effectively …
plays a vital role in downstream tasks such as video browsing and editing. To effectively …
EGGesture: Entropy-Guided Vector Quantized Variational AutoEncoder for Co-Speech Gesture Generation
Y Xiao, K Shu, H Zhang, B Yin, WS Cheang… - Proceedings of the …, 2024 - dl.acm.org
Co-Speech gesture generation encounters challenges with imbalanced, long-tailed gesture
distributions. While recent methods typically address this by employing Vector Quantized …
distributions. While recent methods typically address this by employing Vector Quantized …
MMCOMPOSITION: Revisiting the Compositionality of Pre-trained Vision-Language Models
The advent of large Vision-Language Models (VLMs) has significantly advanced multimodal
understanding, enabling more sophisticated and accurate integration of visual and textual …
understanding, enabling more sophisticated and accurate integration of visual and textual …
Kubrick: Multimodal Agent Collaborations for Synthetic Video Generation
Text-to-video generation has been dominated by end-to-end diffusion-based or
autoregressive models. On one hand, those novel models provide plausible versatility, but …
autoregressive models. On one hand, those novel models provide plausible versatility, but …
STEP: Enhancing Video-LLMs' Compositional Reasoning by Spatio-Temporal Graph-guided Self-Training
Video Large Language Models (Video-LLMs) have recently shown strong performance in
basic video understanding tasks, such as captioning and coarse-grained question …
basic video understanding tasks, such as captioning and coarse-grained question …