6 citations · 17 across the 14 of their papers we have counts for
6 papers · 1 filter
Grounding-Prompter: Prompting LLM with Multimodal Information for Temporal Sentence Grounding in Long Videos
Houlun Chen, Xin Wang, Hong Chen +3
Temporal Sentence Grounding (TSG), which aims to localize moments from videos based on the given natural language queries, has attracted widespread attention. Existing works are ma…
LLM4VG: Large Language Models Evaluation for Video Grounding
Wei Feng, Xin Wang, Hong Chen +7
Recently, researchers have attempted to investigate the capability of LLMs in handling videos and proposed several video LLM models. However, the ability of LLMs to handle video gr…
VTimeLLM: Empower LLM to Grasp Video Moments
Bin Huang, Xin Wang, Hong Chen +2
Large language models (LLMs) have shown remarkable text understanding capabilities, which have been extended as Video LLMs to handle video data for comprehending visual details. Ho…
Lightweight Diffusion Models with Distillation-Based Block Neural Architecture Search
Siao Tang, Xin Wang, Hong Chen +3
Diffusion models have recently shown remarkable generation ability, achieving state-of-the-art performance in many tasks. However, the high computational cost is still a troubling…
Post-training Quantization for Text-to-Image Diffusion Models with Progressive Calibration and Activation Relaxing
Siao Tang, Xin Wang, Hong Chen +4
High computational overhead is a troublesome problem for diffusion models. Recent studies have leveraged post-training quantization (PTQ) to compress diffusion models. However, mos…
VideoDreamer: Customized Multi-Subject Text-to-Video Generation with Disen-Mix Finetuning on Language-Video Foundation Models
Hong Chen, Xin Wang, Guanning Zeng +5
Customized text-to-video generation aims to generate text-guided videos with user-given subjects, which has gained increasing attention. However, existing works are primarily limit…