15 citations · 31 across the 18 of their papers we have counts for
20 papers
Coarse-Grained Predictive Resource Allocation Framework enabling In-Premise XR Collaborations
Sourav Mondal, Elaine Wong
Immersive extended reality (XR) applications are key enablers of human-centric connectivity in next-generation networks. However, meeting their high-throughput, ultra-low-latency,…
4DCodeBench: Benchmarking Agents on Inverse Graphics of Dynamic Scenes
Ruihong Shen, Žiga Kovačič, Peter Kulits +6
We introduce 4DCodeBench, a benchmark for 4D inverse graphics through code generation, in which agents reconstruct dynamic scenes from video as executable graphics programs. To acc…
RealWonder: Real-Time Physical Action-Conditioned Video Generation
Wei Liu, Ziyu Chen, Zizhang Li +3
Current video generation models cannot simulate physical consequences of 3D actions like forces and robotic manipulations, as they lack structural understanding of how actions affe…
PerpetualWonder: Long-Horizon Action-Conditioned 4D Scene Generation
Jiahao Zhan, Zizhang Li, Hong-Xing Yu +1
We introduce PerpetualWonder, a hybrid generative simulator that enables long-horizon, action-conditioned 4D scene generation from a single image. Current works fail at this task b…
ART: Articulated Reconstruction Transformer
Zizhang Li, Cheng Zhang, Zhengqin Li +7
We introduce ART, Articulated Reconstruction Transformer -- a category-agnostic, feed-forward model that reconstructs complete 3D articulated objects from only sparse, multi-state…
Product of Experts for Visual Generation
Yunzhi Zhang, Carson Murtuza-Lanier, Zizhang Li +2
Modern neural models capture rich priors and have complementary knowledge over shared data domains, e.g., images and videos. Integrating diverse knowledge from multiple sources --…
WonderPlay: Dynamic 3D Scene Generation from a Single Image and Actions
Zizhang Li, Hong-Xing Yu, Wei Liu +4
WonderPlay is a novel framework integrating physics simulation with video generation for generating action-conditioned dynamic 3D scenes from a single image. While prior works are…
The Scene Language: Representing Scenes with Programs, Words, and Embeddings
Yunzhi Zhang, Zizhang Li, Matt Zhou +2
We introduce the Scene Language, a visual scene representation that concisely and precisely describes the structure, semantics, and identity of visual scenes. It represents a scene…
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…
ZeroNVS: Zero-Shot 360-Degree View Synthesis from a Single Image
Kyle Sargent, Zizhang Li, Tanmay Shah +8
We introduce a 3D-aware diffusion model, ZeroNVS, for single-image novel view synthesis for in-the-wild scenes. While existing methods are designed for single objects with masked b…
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…
RICO: Regularizing the Unobservable for Indoor Compositional Reconstruction
Zizhang Li, Xiaoyang Lyu, Yuanyuan Ding +3
Recently, neural implicit surfaces have become popular for multi-view reconstruction. To facilitate practical applications like scene editing and manipulation, some works extend th…
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…
A Joint Modeling of Vision-Language-Action for Target-oriented Grasping in Clutter
Kechun Xu, Shuqi Zhao, Zhongxiang Zhou +4
We focus on the task of language-conditioned grasping in clutter, in which a robot is supposed to grasp the target object based on a language instruction. Previous works separately…
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…
MaIL: A Unified Mask-Image-Language Trimodal Network for Referring Image Segmentation
Zizhang Li, Mengmeng Wang, Jianbiao Mei +1
Referring image segmentation is a typical multi-modal task, which aims at generating a binary mask for referent described in given language expressions. Prior arts adopt a bimodal…
Searching for TrioNet: Combining Convolution with Local and Global Self-Attention
Huaijin Pi, Huiyu Wang, Yingwei Li +2
Recently, self-attention operators have shown superior performance as a stand-alone building block for vision models. However, existing self-attention models are often hand-designe…
Learning Part Segmentation through Unsupervised Domain Adaptation from Synthetic Vehicles
Qing Liu, Adam Kortylewski, Zhishuai Zhang +7
Part segmentations provide a rich and detailed part-level description of objects. However, their annotation requires an enormous amount of work, which makes it difficult to apply s…