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20212024
most citedLICHEE: Improving Language Model Pre-training with Multi-grained Tokenization

6 citations · 14 across the 14 of their papers we have counts for

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7 papers · 1 filter

cs.CV2024★ 3 cited

High-Quality Entity Segmentation and Grounding

Lu Qi, Yi-Wen Chen, Tao Zhang +4

In this work, we propose ESG, a pipeline for high-quality entity segmentation and grounding supported by a new dataset EntitySeg. At first, the proposed dataset naming EntitySeg co…

cs.CV2023

UniGS: Unified Representation for Image Generation and Segmentation

Lu Qi, Lehan Yang, Weidong Guo +4

This paper introduces a novel unified representation of diffusion models for image generation and segmentation. Specifically, we use a colormap to represent entity-level masks, add…

cs.CV2023★ 1 cited

AIMS: All-Inclusive Multi-Level Segmentation

Lu Qi, Jason Kuen, Weidong Guo +5

Despite the progress of image segmentation for accurate visual entity segmentation, completing the diverse requirements of image editing applications for different-level region-of-…

cs.CV2023

TCR: Short Video Title Generation and Cover Selection with Attention Refinement

Yakun Yu, Jiuding Yang, Weidong Guo +3

With the widespread popularity of user-generated short videos, it becomes increasingly challenging for content creators to promote their content to potential viewers. Automatically…

cs.CV2023★ 1 cited

GOAL: A Challenging Knowledge-grounded Video Captioning Benchmark for Real-time Soccer Commentary Generation

Ji Qi, Jifan Yu, Teng Tu +12

Despite the recent emergence of video captioning models, how to generate vivid, fine-grained video descriptions based on the background knowledge (i.e., long and informative commen…

cs.CV2022

High-Quality Entity Segmentation

Lu Qi, Jason Kuen, Weidong Guo +5

Dense image segmentation tasks e.g., semantic, panoptic) are useful for image editing, but existing methods can hardly generalize well in an in-the-wild setting where there are unr…

cs.CV2021

CA-SSL: Class-Agnostic Semi-Supervised Learning for Detection and Segmentation

Lu Qi, Jason Kuen, Zhe Lin +7

To improve instance-level detection/segmentation performance, existing self-supervised and semi-supervised methods extract either task-unrelated or task-specific training signals f…