activity
20152026
most citedDeep Joint Task Learning for Generic Object Extraction

37 citations · 102 across the 5 of their papers we have counts for

collaborators
Showing cs.CVShow all

5 papers · 1 filter

cs.CV2026

World Narrative Model for Highly Controllable Video Generation: A Paradigm Shift from Pixel Sampling to Physical World Orchestration

Ye Chen, Xuanhong Chen, Yupeng Zhu +23

The fundamental obstacle to industrial grade video generation is the lack of controllability: existing models treat video as a pixel distribution sampling problem, bypassing the ex…

cs.CV2025★ 1 cited

SVGThinker: Instruction-Aligned and Reasoning-Driven Text-to-SVG Generation

Hanqi Chen, Zhongyin Zhao, Ye Chen +2

Scalable Vector Graphics (SVG) is a code-based representation for 2D visuals. Leveraging recent advances in large language models (LLMs), we study text-to-SVG generation and addres…

cs.CV2015★ 34 cited

Unconstrained Facial Landmark Localization with Backbone-Branches Fully-Convolutional Networks

Zhujin Liang, Shengyong Ding, Liang Lin

This paper investigates how to rapidly and accurately localize facial landmarks in unconstrained, cluttered environments rather than in the well segmented face images. We present a…

cs.CV2015★ 37 cited

Deep Joint Task Learning for Generic Object Extraction

Xiaolong Wang, Liliang Zhang, Liang Lin +2

This paper investigates how to extract objects-of-interest without relying on hand-craft features and sliding windows approaches, that aims to jointly solve two sub-tasks: (i) rapi…

cs.CV2015★ 30 cited

An Expressive Deep Model for Human Action Parsing from A Single Image

Zhujin Liang, Xiaolong Wang, Rui Huang +1

This paper aims at one newly raising task in vision and multimedia research: recognizing human actions from still images. Its main challenges lie in the large variations in human p…