3 citations · 5 across the 6 of their papers we have counts for
6 papers
3D Congealing: 3D-Aware Image Alignment in the Wild
Yunzhi Zhang, Zizhang Li, Amit Raj +5
We propose 3D Congealing, a novel problem of 3D-aware alignment for 2D images capturing semantically similar objects. Given a collection of unlabeled Internet images, our goal is t…
Learning the 3D Fauna of the Web
Zizhang Li, Dor Litvak, Ruining Li +6
Learning 3D models of all animals on the Earth requires massively scaling up existing solutions. With this ultimate goal in mind, we develop 3D-Fauna, an approach that learns a pan…
Learning a Room with the Occ-SDF Hybrid: Signed Distance Function Mingled with Occupancy Aids Scene Representation
Xiaoyang Lyu, Peng Dai, Zizhang Li +4
Implicit neural rendering, which uses signed distance function (SDF) representation with geometric priors (such as depth or surface normal), has led to impressive progress in the s…
Failure-aware Policy Learning for Self-assessable Robotics Tasks
Kechun Xu, Runjian Chen, Shuqi Zhao +5
Self-assessment rules play an essential role in safe and effective real-world robotic applications, which verify the feasibility of the selected action before actual execution. But…
E-NeRV: Expedite Neural Video Representation with Disentangled Spatial-Temporal Context
Zizhang Li, Mengmeng Wang, Huaijin Pi +3
Recently, the image-wise implicit neural representation of videos, NeRV, has gained popularity for its promising results and swift speed compared to regular pixel-wise implicit rep…
Searching Parameterized AP Loss for Object Detection
Chenxin Tao, Zizhang Li, Xizhou Zhu +3
Loss functions play an important role in training deep-network-based object detectors. The most widely used evaluation metric for object detection is Average Precision (AP), which…