51 results on '"Zhikang Zou"'
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2. Parameter-Efficient Fine-Tuning in Spectral Domain for Point Cloud Learning.
3. Uni2Det: Unified and Universal Framework for Prompt-Guided Multi-dataset 3D Detection.
4. Exploring the Causality of End-to-End Autonomous Driving.
5. SOOD++: Leveraging Unlabeled Data to Boost Oriented Object Detection.
6. AVS-Net: Point Sampling with Adaptive Voxel Size for 3D Point Cloud Analysis.
7. PointMamba: A Simple State Space Model for Point Cloud Analysis.
8. Dynamic Adapter Meets Prompt Tuning: Parameter-Efficient Transfer Learning for Point Cloud Analysis.
9. SAM3D: zero-shot 3D object detection via the segment anything model.
10. A Simple Vision Transformer for Weakly Semi-supervised 3D Object Detection.
11. SOOD: Towards Semi-Supervised Oriented Object Detection.
12. CrowdCLIP: Unsupervised Crowd Counting via Vision-Language Model.
13. Diffusion-Based 3D Object Detection with Random Boxes.
14. Understanding Depth Map Progressively: Adaptive Distance Interval Separation for Monocular 3d Object Detection.
15. Repainting and Imitating Learning for Lane Detection.
16. Paint and Distill: Boosting 3D Object Detection with Semantic Passing Network.
17. Query-based Temporal Fusion with Explicit Motion for 3D Object Detection.
18. Attend to Where and When: Cascaded Attention Network for Facial Expression Recognition.
19. SGM3D: Stereo Guided Monocular 3D Object Detection.
20. CrowdCLIP: Unsupervised Crowd Counting via Vision-Language Model.
21. SAM3D: Zero-Shot 3D Object Detection via Segment Anything Model.
22. Diffusion-based 3D Object Detection with Random Boxes.
23. CityTrack: Improving City-Scale Multi-Camera Multi-Target Tracking by Location-Aware Tracking and Box-Grained Matching.
24. SOOD: Towards Semi-Supervised Oriented Object Detection.
25. Multi-Modal 3D Object Detection by Box Matching.
26. Understanding Depth Map Progressively: Adaptive Distance Interval Separation for Monocular 3d Object Detection.
27. The Devil is in the Task: Exploiting Reciprocal Appearance-Localization Features for Monocular 3D Object Detection.
28. Revealing the Reciprocal Relations between Self-Supervised Stereo and Monocular Depth Estimation.
29. Coarse to Fine: Domain Adaptive Crowd Counting via Adversarial Scoring Network.
30. DSANet: Dynamic Segment Aggregation Network for Video-Level Representation Learning.
31. Towards Adversarial Patch Analysis and Certified Defense against Crowd Counting.
32. Crowd Counting via Hierarchical Scale Recalibration Network.
33. HANet: Hybrid Attention-aware Network for Crowd Counting.
34. Fine-grained Iterative Attention Network for Temporal Language Localization in Videos.
35. Leaping from 2D Detection to Efficient 6DoF Object Pose Estimation.
36. Adversarial Category Alignment Network for Cross-domain Sentiment Classification.
37. Paint and Distill: Boosting 3D Object Detection with Semantic Passing Network.
38. Repainting and Imitating Learning for Lane Detection.
39. Attend to count: Crowd counting with adaptive capacity multi-scale CNNs.
40. k-Reciprocal Harmonious Attention Network for Video-Based Person Re-Identification.
41. SGM3D: Stereo Guided Monocular 3D Object Detection.
42. Self-Adaptive Partial Domain Adaptation.
43. Towards Adversarial Patch Analysis and Certified Defense against Crowd Counting.
44. The Devil is in the Task: Exploiting Reciprocal Appearance-Localization Features for Monocular 3D Object Detection.
45. DSANet: Dynamic Segment Aggregation Network for Video-Level Representation Learning.
46. Coarse to Fine: Domain Adaptive Crowd Counting via Adversarial Scoring Network.
47. Crowd Counting via Hierarchical Scale Recalibration Network.
48. DA-Net: Learning the Fine-Grained Density Distribution With Deformation Aggregation Network.
49. Enhanced 3D convolutional networks for crowd counting.
50. Attend To Count: Crowd Counting with Adaptive Capacity Multi-scale CNNs.
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