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Found 5 papers, 2 papers with code
Constrained 6-DoF Grasp Generation on Complex Shapes for Improved Dual-Arm Manipulation
Efficiently generating grasp poses tailored to specific regions of an object is vital for various robotic manipulation tasks, especially in a dual-arm setup.
DiffPrompter: Differentiable Implicit Visual Prompts for Semantic-Segmentation in Adverse Conditions
Furthermore, we investigate the advantages of jointly training visual and latent prompts, demonstrating that this combined approach significantly enhances performance in out-of-distribution scenarios.
HyP-NeRF: Learning Improved NeRF Priors using a HyperNetwork
Neural Radiance Fields (NeRF) have become an increasingly popular representation to capture high-quality appearance and shape of scenes and objects.
GDIP: Gated Differentiable Image Processing for Object-Detection in Adverse Conditions
We present a Gated Differentiable Image Processing (GDIP) block, a domain-agnostic network architecture, which can be plugged into existing object detection networks (e. g., Yolo) and trained end-to-end with adverse condition images such as those captured under fog and low lighting.
Grounding Linguistic Commands to Navigable Regions
We introduce a new dataset, Talk2Car-RegSeg, which extends the existing Talk2car dataset with segmentation masks for the regions described by the linguistic commands.
