83 citations · 353 across the 19 of their papers we have counts for
19 papers
Periodic Vibration Gaussian: Dynamic Urban Scene Reconstruction and Real-time Rendering
Yurui Chen, Chun Gu, Junzhe Jiang +2
Modeling dynamic, large-scale urban scenes is challenging due to their highly intricate geometric structures and unconstrained dynamics in both space and time. Prior methods often…
Enhancing High-Resolution 3D Generation through Pixel-wise Gradient Clipping
Zijie Pan, Jiachen Lu, Xiatian Zhu +1
High-resolution 3D object generation remains a challenging task primarily due to the limited availability of comprehensive annotated training data. Recent advancements have aimed t…
Real-time Photorealistic Dynamic Scene Representation and Rendering with 4D Gaussian Splatting
Zeyu Yang, Hongye Yang, Zijie Pan +1
Reconstructing dynamic 3D scenes from 2D images and generating diverse views over time is challenging due to scene complexity and temporal dynamics. Despite advancements in neural…
SUIT: Learning Significance-guided Information for 3D Temporal Detection
Zheyuan Zhou, Jiachen Lu, Yihan Zeng +2
3D object detection from LiDAR point cloud is of critical importance for autonomous driving and robotics. While sequential point cloud has the potential to enhance 3D perception th…
Generative Semantic Segmentation
Jiaqi Chen, Jiachen Lu, Xiatian Zhu +1
We present Generative Semantic Segmentation (GSS), a generative learning approach for semantic segmentation. Uniquely, we cast semantic segmentation as an image-conditioned mask ge…
Preconditioned Score-based Generative Models
Hengyuan Ma, Xiatian Zhu, Jianfeng Feng +1
Score-based generative models (SGMs) have recently emerged as a promising class of generative models. However, a fundamental limitation is that their sampling process is slow due t…
SeaFormer++: Squeeze-enhanced Axial Transformer for Mobile Visual Recognition
Qiang Wan, Zilong Huang, Jiachen Lu +2
Since the introduction of Vision Transformers, the landscape of many computer vision tasks (e.g., semantic segmentation), which has been overwhelmingly dominated by CNNs, recently…
DeepInteraction: 3D Object Detection via Modality Interaction
Zeyu Yang, Jiaqi Chen, Zhenwei Miao +3
Existing top-performance 3D object detectors typically rely on the multi-modal fusion strategy. This design is however fundamentally restricted due to overlooking the modality-spec…
FashionViL: Fashion-Focused Vision-and-Language Representation Learning
Xiao Han, Licheng Yu, Xiatian Zhu +3
Large-scale Vision-and-Language (V+L) pre-training for representation learning has proven to be effective in boosting various downstream V+L tasks. However, when it comes to the fa…
Vision Transformers: From Semantic Segmentation to Dense Prediction
Li Zhang, Jiachen Lu, Sixiao Zheng +6
The emergence of vision transformers (ViTs) in image classification has shifted the methodologies for visual representation learning. In particular, ViTs learn visual representatio…
Softmax-free Linear Transformers
Jiachen Lu, Junge Zhang, Xiatian Zhu +3
Vision transformers (ViTs) have pushed the state-of-the-art for visual perception tasks. The self-attention mechanism underpinning the strength of ViTs has a quadratic complexity i…
Accelerating Score-based Generative Models with Preconditioned Diffusion Sampling
Hengyuan Ma, Li Zhang, Xiatian Zhu +1
Score-based generative models (SGMs) have recently emerged as a promising class of generative models. However, a fundamental limitation is that their inference is very slow due to…
Accelerating Score-based Generative Models for High-Resolution Image Synthesis
Hengyuan Ma, Li Zhang, Xiatian Zhu +2
Score-based generative models (SGMs) have recently emerged as a promising class of generative models. The key idea is to produce high-quality images by recurrently adding Gaussian…
PolarFormer: Multi-camera 3D Object Detection with Polar Transformer
Yanqin Jiang, Li Zhang, Zhenwei Miao +4
3D object detection in autonomous driving aims to reason "what" and "where" the objects of interest present in a 3D world. Following the conventional wisdom of previous 2D object d…
Learning Ego 3D Representation as Ray Tracing
Jiachen Lu, Zheyuan Zhou, Xiatian Zhu +2
A self-driving perception model aims to extract 3D semantic representations from multiple cameras collectively into the bird's-eye-view (BEV) coordinate frame of the ego car in ord…
Text-Based Person Search with Limited Data
Xiao Han, Sen He, Li Zhang +1
Text-based person search (TBPS) aims at retrieving a target person from an image gallery with a descriptive text query. Solving such a fine-grained cross-modal retrieval task is ch…
SOFT: Softmax-free Transformer with Linear Complexity
Jiachen Lu, Jinghan Yao, Junge Zhang +6
Vision transformers (ViTs) have pushed the state-of-the-art for various visual recognition tasks by patch-wise image tokenization followed by self-attention. However, the employmen…
Simpler is Better: Few-shot Semantic Segmentation with Classifier Weight Transformer
Zhihe Lu, Sen He, Xiatian Zhu +3
A few-shot semantic segmentation model is typically composed of a CNN encoder, a CNN decoder and a simple classifier (separating foreground and background pixels). Most existing me…
TAPAS: Two-pass Approximate Adaptive Sampling for Softmax
Yu Bai, Sally Goldman, Li Zhang
TAPAS is a novel adaptive sampling method for the softmax model. It uses a two pass sampling strategy where the examples used to approximate the gradient of the partition function…