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20142023
most citedSTC: A Simple to Complex Framework for Weakly-supervised Semantic Segmentation

619 citations · 3.7k across the 114 of their papers we have counts for

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Showing 2018Show all

28 papers · 1 filter

cs.CV2018★ 76 cited

Hybrid Knowledge Routed Modules for Large-scale Object Detection

Chenhan Jiang, Hang Xu, Xiangdan Liang +1

The dominant object detection approaches treat the recognition of each region separately and overlook crucial semantic correlations between objects in one scene. This paradigm lead…

cs.LG2018★ 29 cited

AutoLoss: Learning Discrete Schedules for Alternate Optimization

Haowen Xu, Hao Zhang, Zhiting Hu +3

Many machine learning problems involve iteratively and alternately optimizing different task objectives with respect to different sets of parameters. Appropriately scheduling the o…

cs.CV2018★ 39 cited

Soft-Gated Warping-GAN for Pose-Guided Person Image Synthesis

Haoye Dong, Xiaodan Liang, Ke Gong +3

Despite remarkable advances in image synthesis research, existing works often fail in manipulating images under the context of large geometric transformations. Synthesizing person…

cs.CV2018★ 8 cited

Interpretable Visual Question Answering by Reasoning on Dependency Trees

Qingxing Cao, Bailin Li, Xiaodan Liang +1

Collaborative reasoning for understanding image-question pairs is a very critical but underexplored topic in interpretable visual question answering systems. Although very recent s…

cs.CL2018★ 15 cited

Texar: A Modularized, Versatile, and Extensible Toolkit for Text Generation

Zhiting Hu, Haoran Shi, Bowen Tan +12

We introduce Texar, an open-source toolkit aiming to support the broad set of text generation tasks that transform any inputs into natural language, such as machine translation, su…

cs.CV2018★ 2 cited

Adaptive Temporal Encoding Network for Video Instance-level Human Parsing

Qixian Zhou, Xiaodan Liang, Ke Gong +1

Beyond the existing single-person and multiple-person human parsing tasks in static images, this paper makes the first attempt to investigate a more realistic video instance-level…