Search Results for author:
Found 20 papers, 9 papers with code
Rethinking Soft Labels for Knowledge Distillation: A Bias-Variance Tradeoff Perspective
The outputs from the teacher network are used as soft labels for supervising the training of a new network.
Ranked #25 on
Knowledge Distillation
on ImageNet
Track to Detect and Segment: An Online Multi-Object Tracker
Most online multi-object trackers perform object detection stand-alone in a neural net without any input from tracking.
Ranked #1 on
Instance Segmentation
on nuScenes
VarGNet: Variable Group Convolutional Neural Network for Efficient Embedded Computing
In this paper, we propose a novel network design mechanism for efficient embedded computing.
Ranked #5 on
Face Verification
on CFP-FP
NeuRBF: A Neural Fields Representation with Adaptive Radial Basis Functions
The spatial positions of their neural features are fixed on grid nodes and cannot well adapt to target signals.
Unsupervised Domain Adaptive Re-Identification: Theory and Practice
We study the problem of unsupervised domain adaptive re-identification (re-ID) which is an active topic in computer vision but lacks a theoretical foundation.
Ranked #15 on
Unsupervised Domain Adaptation
on Market to Duke
Efficient-3DiM: Learning a Generalizable Single-image Novel-view Synthesizer in One Day
Although the fidelity and generalizability are greatly improved, training such a powerful diffusion model requires a vast volume of training data and model parameters, resulting in a notoriously long time and high computational costs.
Forest R-CNN: Large-Vocabulary Long-Tailed Object Detection and Instance Segmentation
In the classification tree, as the number of parent class nodes are significantly less, their logits are less noisy and can be utilized to suppress the wrong/noisy logits existed in the fine-grained class nodes.
Ranked #5 on
Few-Shot Object Detection
on LVIS v1.0 val
Harnessing Low-Frequency Neural Fields for Few-Shot View Synthesis
We further propose a simple-yet-effective strategy for tuning the frequency to avoid overfitting few-shot inputs: enforcing consistency among the frequency domain of rendered 2D images.
Relit-NeuLF: Efficient Relighting and Novel View Synthesis via Neural 4D Light Field
A DecomposeNet learns to map each ray to its SVBRDF components: albedo, normal, and roughness.
Neurons Merging Layer: Towards Progressive Redundancy Reduction for Deep Supervised Hashing
It generates hashing bits by the output neurons of a deep hashing network.
Joint Neural Architecture Search and Quantization
Here our goal is to automatically find a compact neural network model with high performance that is suitable for mobile devices.
Rethinking Soft Labels for Knowledge Distillation: A Bias–Variance Tradeoff Perspective
In this paper, we investigate the bias-variance tradeoff brought by distillation with soft labels.
NeuLF: Efficient Novel View Synthesis with Neural 4D Light Field
In this paper, we present an efficient and robust deep learning solution for novel view synthesis of complex scenes.
Stacked Homography Transformations for Multi-View Pedestrian Detection
This task is confronted with two challenges: how to establish the 3D correspondences from views to the BEV map and how to assemble occupancy information across views.
Ranked #7 on
Multiview Detection
on MultiviewX
PREF: Predictability Regularized Neural Motion Fields
We propose to regularize the estimated motion to be predictable.
Federated Learning with Privacy-Preserving Ensemble Attention Distillation
We propose a privacy-preserving FL framework leveraging unlabeled public data for one-way offline knowledge distillation in this work.
NeRFPlayer: A Streamable Dynamic Scene Representation with Decomposed Neural Radiance Fields
Visually exploring in a real-world 4D spatiotemporal space freely in VR has been a long-term quest.
Progressive Multi-view Human Mesh Recovery with Self-Supervision
To date, little attention has been given to multi-view 3D human mesh estimation, despite real-life applicability (e. g., motion capture, sport analysis) and robustness to single-view ambiguities.
RoomDreamer: Text-Driven 3D Indoor Scene Synthesis with Coherent Geometry and Texture
The proposed framework consists of two significant components: Geometry Guided Diffusion and Mesh Optimization.
Efficient-NeRF2NeRF: Streamlining Text-Driven 3D Editing with Multiview Correspondence-Enhanced Diffusion Models
In this work, we propose that by incorporating correspondence regularization into diffusion models, the process of 3D editing can be significantly accelerated.
