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Found 25 papers, 11 papers with code
SG-Tailor: Inter-Object Commonsense Relationship Reasoning for Scene Graph Manipulation
Scene graphs capture complex relationships among objects, serving as strong priors for content generation and manipulation.
Think Before Refusal : Triggering Safety Reflection in LLMs to Mitigate False Refusal Behavior
Recent advancements in large language models (LLMs) have demonstrated that fine-tuning and human alignment can render LLMs harmless.
Every FLOP Counts: Scaling a 300B Mixture-of-Experts LING LLM without Premium GPUs
Ultimately, our experimental findings demonstrate that a 300B MoE LLM can be effectively trained on lower-performance devices while achieving comparable performance to models of a similar scale, including dense and MoE models.
MMGDreamer: Mixed-Modality Graph for Geometry-Controllable 3D Indoor Scene Generation
Controllable 3D scene generation has extensive applications in virtual reality and interior design, where the generated scenes should exhibit high levels of realism and controllability in terms of geometry.
VideoINSTA: Zero-shot Long Video Understanding via Informative Spatial-Temporal Reasoning with LLMs
The challenge of information redundancy in long videos prompts the question of what specific information is essential for large language models (LLMs) and how to leverage them for complex spatial-temporal reasoning in long-form video analysis.
EchoScene: Indoor Scene Generation via Information Echo over Scene Graph Diffusion
The scheme ensures that the denoising processes are influenced by a holistic understanding of the scene graph, facilitating the generation of globally coherent scenes.
GeoGaussian: Geometry-aware Gaussian Splatting for Scene Rendering
During the Gaussian Splatting optimization process, the scene's geometry can gradually deteriorate if its structure is not deliberately preserved, especially in non-textured regions such as walls, ceilings, and furniture surfaces.
HouseCat6D - A Large-Scale Multi-Modal Category Level 6D Object Perception Dataset with Household Objects in Realistic Scenarios
Estimating 6D object poses is a major challenge in 3D computer vision.
SecondPose: SE(3)-Consistent Dual-Stream Feature Fusion for Category-Level Pose Estimation
Leveraging the advantage of DINOv2 in providing SE(3)-consistent semantic features, we hierarchically extract two types of SE(3)-invariant geometric features to further encapsulate local-to-global object-specific information.
SG-Bot: Object Rearrangement via Coarse-to-Fine Robotic Imagination on Scene Graphs
In this paper, we present SG-Bot, a novel rearrangement framework that utilizes a coarse-to-fine scheme with a scene graph as the scene representation.
CCD-3DR: Consistent Conditioning in Diffusion for Single-Image 3D Reconstruction
However, such strategies fail to consistently align the denoised point cloud with the given image, leading to unstable conditioning and inferior performance.
On the Importance of Accurate Geometry Data for Dense 3D Vision Tasks
Learning-based methods to solve dense 3D vision problems typically train on 3D sensor data.
IPCC-TP: Utilizing Incremental Pearson Correlation Coefficient for Joint Multi-Agent Trajectory Prediction
Reliable multi-agent trajectory prediction is crucial for the safe planning and control of autonomous systems.
HouseCat6D -- A Large-Scale Multi-Modal Category Level 6D Object Perception Dataset with Household Objects in Realistic Scenarios
Estimating 6D object poses is a major challenge in 3D computer vision.
OPA-3D: Occlusion-Aware Pixel-Wise Aggregation for Monocular 3D Object Detection
Despite monocular 3D object detection having recently made a significant leap forward thanks to the use of pre-trained depth estimators for pseudo-LiDAR recovery, such two-stage methods typically suffer from overfitting and are incapable of explicitly encapsulating the geometric relation between depth and object bounding box.
MonoGraspNet: 6-DoF Grasping with a Single RGB Image
6-DoF robotic grasping is a long-lasting but unsolved problem.
DA$^2$ Dataset: Toward Dexterity-Aware Dual-Arm Grasping
In this paper, we introduce DA$^2$, the first large-scale dual-arm dexterity-aware dataset for the generation of optimal bimanual grasping pairs for arbitrary large objects.
Is my Depth Ground-Truth Good Enough? HAMMER -- Highly Accurate Multi-Modal Dataset for DEnse 3D Scene Regression
Depth estimation is a core task in 3D computer vision.
FlowMOT: 3D Multi-Object Tracking by Scene Flow Association
Most end-to-end Multi-Object Tracking (MOT) methods face the problems of low accuracy and poor generalization ability.
Semantic Graph Based Place Recognition for 3D Point Clouds
First, we propose a novel semantic graph representation for the point cloud scenes by reserving the semantic and topological information of the raw point cloud.
PASS3D: Precise and Accelerated Semantic Segmentation for 3D Point Cloud
In this paper, we propose PASS3D to achieve point-wise semantic segmentation for 3D point cloud.
PoseConvGRU: A Monocular Approach for Visual Ego-motion Estimation by Learning
The feature-encoding module encodes the short-term motion feature in an image pair, while the memory-propagating module captures the long-term motion feature in the consecutive image pairs.
