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20152022
most citedFully Connected Deep Structured Networks

263 citations · 806 across the 42 of their papers we have counts for

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49 papers · 1 filter

cs.CV20222 cited

Learnable Polyphase Sampling for Shift Invariant and Equivariant Convolutional Networks

Renan A. Rojas-Gomez, Teck-Yian Lim, Alexander G. Schwing +2

We propose learnable polyphase sampling (LPS), a pair of learnable down/upsampling layers that enable truly shift-invariant and equivariant convolutional networks. LPS can be train…

cs.CV20221 cited

Controllable Radiance Fields for Dynamic Face Synthesis

Peiye Zhuang, Liqian Ma, Oluwasanmi Koyejo +1

Recent work on 3D-aware image synthesis has achieved compelling results using advances in neural rendering. However, 3D-aware synthesis of face dynamics hasn't received much attent…

cs.CV20228 cited

Learning to Decompose Visual Features with Latent Textual Prompts

Feng Wang, Manling Li, Xudong Lin +3

Recent advances in pre-training vision-language models like CLIP have shown great potential in learning transferable visual representations. Nonetheless, for downstream inference,…

cs.CV2022

Neural Volumetric Object Selection

Zhongzheng Ren, Aseem Agarwala, Bryan Russell +2

We introduce an approach for selecting objects in neural volumetric 3D representations, such as multi-plane images (MPI) and neural radiance fields (NeRF). Our approach takes a set…

cs.CV20221 cited

Joint Forecasting of Panoptic Segmentations with Difference Attention

Colin Graber, Cyril Jazra, Wenjie Luo +2

Forecasting of a representation is important for safe and effective autonomy. For this, panoptic segmentations have been studied as a compelling representation in recent work. Howe…

cs.CV2022

Total Variation Optimization Layers for Computer Vision

Raymond A. Yeh, Yuan-Ting Hu, Zhongzheng Ren +1

Optimization within a layer of a deep-net has emerged as a new direction for deep-net layer design. However, there are two main challenges when applying these layers to computer vi…